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  • Books  (25)
  • Articles  (170,945)
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  • 1
    Electronic Resource
    Electronic Resource
    News (1999)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 16 (1999), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00120
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  • 2
    Electronic Resource
    Electronic Resource
    Diary (1999)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 16 (1999), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00121
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  • 3
    Electronic Resource
    Electronic Resource
    Representing diverse mathematical problems using neural networks in hybrid intelligent systems (1999)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 16 (1999), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: In recent years, artificial neural networks have attracted considerable attention as candidates for novel computational systems. Computer scientists and engineers are developing neural networks as representational and computational models for problem solving: neural networks are expected to produce new solutions or alternatives to existing models. This paper demonstrates the flexibility of neural networks for modeling and solving diverse mathematical problems including Taylor series expansion, Weierstrass’s first approximation theorem, linear programming with single and multiple objectives, and fuzzy mathematical programming. Neural network representations of such mathematical problems may make it possible to overcome existing limitations, to find new solutions or alternatives to existing models, and to achieve synergistic effects through hybridization.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00118
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  • 4
    Electronic Resource
    Electronic Resource
    Comparing neural network approximations for different functional forms (1999)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 16 (1999), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: This paper examines the capacity of feedforward neural networks (NNs) to approximate certain functional forms. Its purpose is to show that the theoretical property of ‘universal approximation’, which provides the basic rationale behind the NN approach, should not be interpreted too literally. The most important issue considered involves the number of hidden layers in the network. We show that for a number of interesting functional forms better generalization is possible with more than one hidden layer, despite theoretical results to the contrary. Our experiments constitute a useful set of counter-examples.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00096
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  • 5
    Electronic Resource
    Electronic Resource
    Book Reviews (1999)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 16 (1999), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: John McCardle, Neural Network Systems Techniques and Applications
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00090
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  • 6
    Electronic Resource
    Electronic Resource
    An interactive tool for knowledge base refinement (1999)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 16 (1999), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: We present a tool that combines two main trends of knowledge base refinement. The first is the construction of interactive knowledge acquisition tools and the second is the development of machine learning methods that automate this procedure. The tool presented here is interactive and gives experts the ability to evaluate an expert system and provide their own diagnoses on specific problems, when the expert system behaves erroneously. We also present a database scheme that supports the collection of specific instances. The second aspect of the tool is that knowledge base refinement and machine learning methods can be applied to the database, in order to automate the procedure refining the knowledge base. In this paper we examine the application of inductive learning algorithms within the proposed framework. Our main goal is to encourage the experts to evaluate expert systems and to introduce new knowledge, based on their experience.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00087
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  • 7
    Electronic Resource
    Electronic Resource
    Neural network analysis and the characteristics of market sentiment in the financial markets (2000)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 17 (2000), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: The properties of a modular neural network system designed to forecast movements of the long gilt futures contract are examnined. The examination illustrates that diagnostic measures can effectively inform end-users of the system when appropriately to switch modules given the likelihood of the degradation of forecasts. The modelling is based upon periods of market sentiment, and the inductive data models encapsulated, within the modules of the neural network system, are investigated. The models track, and also provide knowledge of , underlying market characteristics in different periods of market sentiment. The research provides deductions concerning the (dis-)similarity of underlying characteristics in differing periods of market sentiment.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00141
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  • 8
    Electronic Resource
    Electronic Resource
    Diagnostic expert systems: a method for engineering knowledge used in sequential diagnosis (2000)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 17 (2000), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: The paper presents a method for helping knowledge engineers in modelling the knowledge involved in sequential diagnosis. In particular, we consider sequential diagnosis as a process which occurs in the following type of scenario: (1) there exist some candidate hypotheses which are to be pursued; (2) for each hypothesis there are some alternative tests which might be executed to pursue it; (3) the available knowledge about the world precludes projecting into the future (in other words, the available knowledge about the world does not afford the information needed for planning sequences of tests, i.e. for projecting the consequences of possible sequences of actions and picking the best sequence); (4) the choice of the next test (or tests) is made on the basis of the current state of knowledge; (5) the outcome of a test execution is affected by uncertainty. The suggested method addresses the problem of engineering the knowledge experts use for making decisions under uncertainty. A practical example of the method is also presented: at any time of the diagnostic process the expert is provided with a dynamically updated list of suggested tests in order to support him or her in the decision-making problem about which test to execute next.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00142
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  • 9
    Electronic Resource
    Electronic Resource
    Internet-based expert systems (2000)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 17 (2000), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: The Internet offers a large potential for delivery of various information-based services, including the services of intelligent applications. As the availability of the Internet has grown, its value as a medium for the delivery of expert systems in particular has increased. There are now a large number of expert systems available on the Internet, including applications in industry, medicine, science and government. Though the Internet provides several advantages for expert system development, it also presents some special problems. These advantages and disadvantages are explored in more detail in this paper. The paper also presents a review of several Internet-based expert systems with a representative sample of publicly available applications, and a discussion of typical tools for developing Internet-based expert systems. A case study of an Internet-based expert system is presented as well.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00135
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  • 10
    Electronic Resource
    Electronic Resource
    Connectionist symbolic rule encoding using a generalized phase-locking mechanism (2000)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 17 (2000), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: This paper describes a connectionist inference architecture which performs standard symbolic inference on a subclass of first-order predicate calculus. This work first involves constructing efficient connectionist mechanisms to represent basic symbol components, dynamic bindings and basic symbolic inference procedures, and devising a set of algorithms which automatically translates input descriptions to localist neural networks. These connectionist mechanisms are built by taking an existing phase-locking mechanism and extending it further to obtain desirable features to represent and manipulate basic symbol structures. The existing phase-locking mechanism represents dynamic bindings very efficiently using temporal synchronous activity between neuron elements but has fundamental limitations in supporting standard symbolic inference. The extension addresses these limitations. The extended system encodes a significant subset of a Horn clause language in a connectionist style.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00124
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  • 11
    Electronic Resource
    Electronic Resource
    Fractal encoding of context-free grammars in connectionist networks (2000)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 17 (2000), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Connectionist network learning of context-free languages has so far been applied only to very simple cases and has often made use of an external stack. Learning complex context-free languages with a homogeneous neural mechanism looks like a much harder problem. The current paper takes a step toward solving this problem by analyzing context-free grammar computation (without addressing learning) in a class of analog computers called dynamical automata, which are naturally implemented in connectionist networks. The result is a widely applicable method of using fractal sets to organize infinite-state computations in a bounded state space. An appealing consequence is the development of parameter-space maps, which locate various complex computers in spatial relationships to one another. An example suggests that such a global perspective on the organization of the parameter space may be helpful for solving the hard problem of getting connectionist networks to learn complex grammars from examples.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00126
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  • 12
    Electronic Resource
    Electronic Resource
    Analogy retrieval and processing with distributed vector representations (2000)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 17 (2000), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Holographic reduced representations (HRRs) are a method for encoding nested relational structures in fixed-width vector representations. HRRs encode relational structures as vector representations in such a way that the superficial similarity of the vectors reflects both superficial and structural similarity of the relational structures. HRRs also support a number of operations that could be very useful in psychological models of human analogy processing: fast estimation of superficial and structural similarity via a vector dot-product; finding corresponding objects in two structures; and chunking of vector representations. Although similarity assessment and discovery of corresponding objects both theoretically take exponential time to perform fully and accurately, with HRRs one can obtain approximate solutions in constant time. The accuracy of these operations with HRRs mirrors patterns of human performance on analog retrieval and processing tasks.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00125
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  • 13
    Electronic Resource
    Electronic Resource
    News (2000)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 17 (2000), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00127
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  • 14
    Electronic Resource
    Electronic Resource
    Diary (2000)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 17 (2000), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00128
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  • 15
    Electronic Resource
    Electronic Resource
    Editorial (1999)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 16 (1999), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00113
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  • 16
    Electronic Resource
    Electronic Resource
    Integrating symbolic and numerical features for fault prediction and diagnosis by an expert system (1999)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 16 (1999), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: This paper addresses the topic of a predictive task after integration of symbolic and numerical features by a hybrid diagnostic expert system. The online interaction of information and knowledge from various sources is achieved after successful combination of different development environments, tools and programs. The system infers using cooperatively dynamic modelling information, online sensor information, and stored knowledge in the knowledge base.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00114
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  • 17
    Electronic Resource
    Electronic Resource
    A hybrid knowledge-based system applied to epidemic screening (1999)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 16 (1999), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Although many knowledge-based systems (KBSs) focus on single-paradigm approaches to encoding knowledge (such as production rules), experts rarely use a single type of knowledge in solving a problem. More often, an expert will apply a number of reasoning mechanisms. In recent years, rule-based reasoning (RBR), case-based reasoning (CBR) and model-based reasoning (MBR) have emerged as important and complementary reasoning methodologies in artificial intelligence. For complex problem solving, it is useful to integrate RBR, CBR and MBR. In this paper, a hybrid KBS which integrates a deductive RBR system, an inductive CBR system and a quantitative MBR system is proposed for epidemic screening. The system has been tested using real data, and results are encouraging.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00116
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  • 18
    Electronic Resource
    Electronic Resource
    Dynamic recurrent neural networks for a hybrid intelligent decision support system for the metallurgical industry (1999)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 16 (1999), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Knowledge-based modeling and implementation of the various manufacturing processes represent an intensive research area. It is known that it is difficult to analyze the mechanisms of many industrial production processes and build dynamic models by employing classical methods for intelligent systems in manufacturing. This paper describes how to use dynamic recurrent neural networks to provide the model base of a hybrid intelligent system for the metallurgical industry with a quality control model. The hybrid system extracts the features of image sequences obtained through the vision detection subsystem and employs a dynamic recurrent neural network to assess and predict the product qualities to further coordinate the entire production process.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00115
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  • 19
    Electronic Resource
    Electronic Resource
    Proposing an architectural framework of a hybrid knowledge-based system for production rescheduling (1999)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 16 (1999), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: An architectural configuration of a knowledge-based system for production rescheduling reported in this paper uncovers a number of points of interest to practitioners as well as researchers. The study shows that knowledge-based methods applied to production rescheduling are a valuable approach for manufacturers to manage production disturbances and deliver customer orders on time. Very often, developing an effective scheduling system whilst solving some problems requires an appropriate combination of a rigorous analysis of the production system state and the rules of thumb used by the human scheduler. In the actual performance of this hybrid system, an expert simulation system was used to produce new schedules that fit the real production environment.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00119
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  • 20
    Electronic Resource
    Electronic Resource
    AI in the next millennium (1999)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 16 (1999), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00103
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  • 21
    Electronic Resource
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    Expert knowledge acquisition and the unwilling expert: a knowledge engineering perspective (1999)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 16 (1999), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Expert systems are an evolving technology with the potential to make human expertise widely and cheaply available. The literature describing the development of expert systems generally assumes that experts willingly give up their knowledge. This is unrealistic and may be a reason why most expert system projects fail. This paper explores the problem of unwilling experts from the perspective of a knowledge engineer building an expert system. The link between knowledge and organizational power is established and human motivation theories are discussed. Finally, a new motivational approach is introduced to help the knowledge engineer deal with unwilling experts.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00104
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  • 22
    Electronic Resource
    Electronic Resource
    A knowledge sorting process for a product design expert system (1999)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 16 (1999), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Knowledge sorting is one way to organize the knowledge acquired from the domain expert(s) and various sources. Well-organized knowledge representation will make rule extraction much easier. This paper describes a knowledge sorting process that was developed to facilitate the rule extraction for a product design expert system. The process capitalizes on the relationships between design attributes and factors, dependent and independent variables, and consists of three stages: identification of knowledge sources, generation of taxonomic trees, and organization of acquired knowledge. An example applies the sorting process to the development of an expert system for the design of wood head golf clubs.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00106
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  • 23
    Electronic Resource
    Electronic Resource
    The rise and ‘fall’ of expert systems in medicine (1999)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 16 (1999), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: This paper represents a personal perspective on the last 13 years of research in medical artificial intelligence and expert systems, and describes the progress of the discipline from its inception to its current status. The challenges faced by researchers are examined, and it is argued that (despite the claims) theoretical and technical limitations are not the major barriers to the successful implementation of medical artificial intelligence and expert systems, but rather more complex professional and organizational issues are at stake.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00107
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  • 24
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    A function-centered framework for reasoning about system failure at multiple levels of abstraction (1999)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 16 (1999), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: This paper presents the knowledge organization for a simulation subsystem that is a component of a comprehensive expert system for failure modes and effects analysis. Organizing the simulation subsystem’s knowledge base around a function-centered ontology produces an architecture that facilitates reasoning about an engineering design at multiple levels of abstraction and throughout the life-cycle of the design. Moreover, the resulting architecture provides the capability for incorporating computer-aided analysis and design tools early on into the conceptual design of an engineering system before a commitment is made to a specific technology to implement the system’s behavior. The result is an expert system simulation knowledge source that can be used to reason about the effects of system failures based on conceptual designs, i.e. designs in which commitments to an underlying technology to achieve the system’s function have not yet been made but computer-aided assistance for reasoning about the system’s potential failure modes and effects is useful.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00105
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  • 25
    Electronic Resource
    Electronic Resource
    Connectionist variable binding (1999)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 16 (1999), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Variable binding has long been a challenge to connectionists. Attempts to perform variable binding using localist and distributed connectionist representations are discussed, and problems inherent in each type of representation are outlined.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00108
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  • 26
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    Book Reviews (1999)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 16 (1999), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Books reviewed:Daniel Kustrin, Neural Network Analysis, Architectures and ApplicationsSimon O’Keefe, Fuzzy and Neural Approaches in EngineeringJohn McCardle, Neural Network Systems Techniques and Application
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    URL: http://dx.doi.org/10.1111/1468-0394.00109
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  • 27
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    The Department of Trade and Industry’s Smart Systems for Decision Makers initiative (1999)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 16 (1999), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00110
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  • 28
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    News (1999)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 16 (1999), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00111
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  • 29
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    Diary (1999)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 16 (1999), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00112
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  • 30
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    Foreword (1999)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 16 (1999), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00094
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  • 31
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    Symbol processing — a challenge for neural networks? (1999)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 16 (1999), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00095
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  • 32
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    Extending CLIPS to support temporal representation and reasoning (1999)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 16 (1999), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Applications using expert systems for monitoring and control problems often require the ability to represent temporal knowledge and to apply reasoning based on that knowledge. Incorporating temporal representation and reasoning into expert systems leads to two problems in development: dealing with an implied temporal order of events using a non-procedural tool; and maintaining the large number of temporal relations that can occur among facts in the knowledge base. In this paper we explore these problems by using an expert system shell, CLIPS (C Language Integrated Production System), to create temporal relations using common knowledge-based constructs. We also build an extension to CLIPS through a user-defined function which generates the temporal relations from those facts. We use the extension to create and maintain temporal relations in a workflow application that monitors and controls an engineering design change review process. We also propose a solution to ensure truth maintenance among temporally related facts that links our temporal extension to the CLIPS facility for truth maintenance.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00097
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    Development of a fuzzy push delivery scheme for Internet sites (1999)
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    Notes: Push technology is the term recently linked with Web-based products to indicate the built-in capability of the software package to deliver relevant information to the user automatically. In this paper, a fuzzy push delivery scheme is described which ‘observes’ the movements of the user within the Web pages and then evaluates the personal interests and preferences of the user. With the information available from the fuzzy scheme, Web site information favoured by visitors can be ‘pushed’ to them without even being requested. To verify the feasibility of the concept, a Web site with various shopping spots has been developed with built-in functions to detect the time of stay in various sites by visitors . Output from the proposed fuzzy scheme is compared with the perception of the interest level given by the visitors themselves for its evaluation. The built-in feature of the scheme can significantly enhance the functionality and attractiveness of the Web site involved and hence improve its competitiveness in the global market. The development of the proposed scheme and its evaluation in an emulated Internet environment are covered in the paper.
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    An online expert system for fault diagnosis in hydraulic systems (1999)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
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    Notes: Fault diagnosis has become increasingly important for industrial automation and many approaches have been investigated for the online diagnostic task. This work demonstrates a new online expert system for dynamic industrial automated processes. The emphasis of this diagnostic system lies in the functions provided for fault detection, prediction, compensation and diagnosis. The system uses experiential knowledge cooperatively with scientific knowledge in a new interactive formation. It is developed in two parts using the DASYLab software for the numerical computations and the KPWin development tool for the symbolic representations. The system was developed in collaboration with the company Automation Systems S.A., which specializes in hydraulic systems, and is used for fault detection in production machines.
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    Facilitating the use of multi-attribute utility theory in expert systems:an aid for identifying the right relative importance weights of attributes (1999)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
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    Notes: In general, expert system applications to real cases involve making decisions, i.e. selecting a suitable action among a set of possible alternative actions. A well-known standard method for modelling decision problems is the so-called multi-attribute utility theory (MAUT), a method in which the alternatives are viewed in terms of their attributes. A set of attributes are identified and a specific value and a suitable relative importance weight are assigned to each attribute. However, it is not easy for the expert to quantify the relative importance weight of an attribute: this assignment entails a certain abstraction activity from the expert and, as is well known, experts have difficulty in providing their knowledge in abstract and general terms. In order to overcome this difficulty we propose a method for automatically inferring relative importance weights from a set of specific action sequences. An action sequence is a list in chronological order of the actions executed by the expert when facing specific cases of decision problems. Providing action sequences requires no other effort but remembering specific episodes, and this task is much easier for experts than having to directly provide precise numbers expressing relative importance weights. Moreover in many cases action sequences are already stored in suitable records. Consider, for example, the list of medical tests executed on a given patient, a list included in the patient clinical record stored in the clinical database of a hospital. On the basis of these considerations the proposed method should be useful for designers of expert systems which face problems of choosing the right action among a set of alternative actions.
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    Editorial (1999)
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    Classification and rule induction using rough set theory (2000)
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    Notes: Rough set theory (RST) offers an interesting and novel approach both to the generation of rules for use in expert systems and to the traditional statistical task of classification. The method is based on a novel classification metric, implemented as upper and lower approximations of a set and more generally in terms of positive, negative and boundary regions. Classification accuracy, which may be set by the decision maker, is measured in terms of conditional probabilities for equivalence classes, and the method involves a search for subsets of attributes (called ’reducts’) which do not require a loss of classification quality. To illustrate the technique, RST is employed within a state level comparison of education expenditure in the USA.
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    Feedforward networks in financial predictions: the future that modifies the present (2000)
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    Notes: The main goal of this paper is to show how relatively minor modifications of well-known algorithms (in particular, back propagation) can dramatically increase the performance of an artificial neural network (ANN) for time series prediction. We denote our proposed sets of modifications as the ’self-momentum’, ’Freud’ and ’Jung’ rules. In our opinion, they provide an example of an alternative approach to the design of learning strategies for ANNs, one that focuses on basic mathematical conceptualization rather than on formalism and demonstration. The complexity of actual prediction problems makes it necessary to experiment with modelling possibilities whose inherent mathematical properties are often not well understood yet. The problem of time series prediction in stock markets is a case in point. It is well known that asset price dynamics in financial markets are difficult to trace, let alone to predict with an operationally interesting degree of accuracy. We therefore take financial prediction as a meaningful test bed for the validation of our techniques. We discuss in some detail both the theoretical underpinnings of the technique and our case study about financial prediction, finding encouraging evidence that supports the theoretical and operational viability of our new ANN specifications. Ours is clearly only a preliminary step. Further developments of ANN architectures with more and more sophisticated ’learning to learn’ characteristics are now under study and test.
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    Knowledge-based system for telecontrol of anaerobic wastewater treatment plants (2000)
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    Notes: This paper describes the design and implementation of an intelligent real-time supervision system for the monitoring and control of wastewater treatment plants. The system presents a hybrid structure which integrates knowledge engineering techniques and methodologies (an expert system based on production rules embodying non-mathematical or semiquantitative knowledge of unit operation) and algorithmic process-related methods (data acquisition, signal preprocessing, calculation of plant operation parameters etc.). The fundamental design aspects consist of temporal information treatment, artifact detection and a client- server structure which allows the telesupervision of various plants by a central system.
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    A hybrid system applied to epidemic screening (2000)
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    Expert systems 17 (2000), S. 0 
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    Notes: Although many knowledge-based systems (KBSs) focus on single-paradigm approaches to encoding knowledge (such as production rules), human experts rarely use a single type of knowledge to solve a real-world problem. A human expert usually combines a number of reasoning mechanisms. In recent years, rule-based reasoning (RBR), case-based reasoning (CBR) and model-based reasoning (MBR) have emerged as important and complementary reasoning methodologies in the intelligent systems area. For complex problem solving, it is useful to integrate RBR, CBR and MBR. In this paper, a hybrid epidemic screening KBS which integrates a deductive RBR system, an inductive CBR system and a quantitative MBR system is proposed. The system has been tested using real epidemic screening variables and data.
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    GDKAT: A goal-driven knowledge acquisition tool for knowledge base development (2000)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
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    Notes: While knowledge-based systems are being used extensively to assist in making decisions, a critical factor that affects their performance and reliability is the quantity and quality of the knowledge bases. Knowledge acquisition requires the design and development of an in-depth comprehension of knowledge modeling and of applicable domain. Many knowledge acquisition tools have been developed to support knowledge base development. However, a weakness that is revealed in these tools is the domain-dependent and complex acquisition process. Domain dependence limits the applicable areas and the complex acquisition process makes the tool difficult to use. In this paper, we present a goal-driven knowledge acquisition tool (GDKAT) that helps elicit and store experts’ declarative and procedural knowledge in knowledge bases for a user-defined domain. The designed tool is implemented using the object-oriented design methodology under C++ Windows environment. An example that is used to demonstrate the GDKAT is also delineated. While the application domain for the example presented is reflow soldering in surface mount printed circuit board assembly, the GDKAT can be used to develop knowledge bases for other domains also.
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    A connectionist inference model for pattern-directed knowledge representation (2000)
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    Notes: In this paper we propose a connectionist model for variable binding. The model is topology dependent on the graph it builds based on the predicates available. The irregular connections between perceptron-like assemblies facilitate forward and backward chaining. The model treats the symbolic data as a sequence and represents the training set as a partially connected network using basic set and graph theory to form the internal representation. Inference is achieved by opportunistic reasoning via the bidirectional connections. Consequently, such activity stabilizes to a multigraph. This multigraph is composed of isomorphic subgraphs which all represent solutions to the query made. Such a model has a number of advantages over other methods in that irrelevant connections are avoided by superimposing positionally dependent sub-structures that are identical, variable binding can be encoded and multiple solutions can be extracted simultaneously. The model also has the ability to adapt its existing architecture when presented with new clauses and therefore add new relationships/rules to the model explicitly; this is done by some partial retraining of the network due to the superimposition properties.
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    Editorial: Symbol processing in connectionist systems (2000)
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    A connectionist production system which can perform both modus ponens and modus tollens simultaneously (2000)
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    Notes: Modus ponens is used in forward inference and backward inference, where the truth of the conclusion is inferred from the truth of the premise. In modus tollens, the falseness of the premise is inferred from the falseness of the conclusion. Although modus ponens is used in general connectionist production systems, modus tollens is rarely used, except in Quinlan’s proposed INFERNO system and in the system proposed by Thornber. A connectionist production system called ConnPS that can perform both modus ponens and modus tollens simultaneously is described. Compared to the INFERNO system, one of the advantages of ConnPS is its supervised learning ability. The rules and examples given as external knowledge are often erroneous and incomplete. In ConnPS, these rules can be refined by using the supervised learning. Both positive and negative examples are presented to ConnPS, onto which the external rules and observations are mapped. Moreover, ConnPS’s implementations of implications, conjunctions, disjunctions and negation are intuitively consistent with Boolean logic.
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    Hybrid artificial intelligence approach to urban planning (1999)
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    Notes: Knowledge-based modeling and implementation of the various urban planning processes represent an intensive research area. This paper presents a hybrid artificial intelligence system using a knowledge-based approach, neural networks and fuzzy logic that automates the decision-making process in urban planning. The system is used for developing urban development alternatives based on real-world data. Results show that, by integrating knowledge-based systems, artificial neural networks and fuzzy systems, the system achieves improvements in the implementation of each respective system as well as an increase in the breadth of functionality within the application. With this approach, the best of three technologies can be compiled together to solve complex urban problems. We discuss the structure of the combined technologies, as well as providing examples of its application in the field of urban development.
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    ICADS: Intelligent Car Audio Design System for product planning (1999)
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    Notes: This paper describes the development of a system, ICADS (Intelligent Car Audio Design System), that can be used to effectively support product development engineers in car audio product design. We have demonstrated the use of expert system technology and the technique of quality function deployment (QFD) in supporting car audio design planning. QFD is applied as a knowledge acquisition method in this study to support car audio design teams in the development of products in a structured way that relates market demand via engineering specifications to parts specifications. We believe that other industries can use a similar approach for developing an expert system that can support product design planning.
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    An actor model for rule-based systems (1999)
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    Notes: Our research originates from a study of the possibilities of integrating rules and objects in knowledge-based systems. In the present work, we are interested in the interactionist perspective of an object. The stepwise reasoning of a diagnostic expert system, possibly involving subgoaling and interactions with the environment, can be easily codified by means of production rules over proposition literals. This set of rules can be graphically represented in a network manner denoting the relations between the rules. The individual nodes in the network can be expressed by means of autonomous objects and their relations, interpreted as possible communications between them. The objects are given a structure and a proper behaviour and cooperate for performing logical reasoning by means of forward and backward chaining inference processes. Therefore, designing this system implies addressing several basic issues such as inter-object communications and their synchronization. The problem here is not necessarily to develop a great intelligence locally but to develop strong networks of good communicators. This approach belongs to the interactionist representation current, where objects are called actors. In principle, the actors may carry out computation in parallel and provide a conceptual foundation for massively concurrent object-oriented paradigms. From this point of view, a system allowing for the simultaneous investigation of several rules and premises in the forward or the backward chaining would be significantly more efficient.
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    A hierarchical expert system for integrated scheduling of ship berthing, discharging and material transport (1998)
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    Expert systems 15 (1998), S. 0 
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    Notes: Abstract: Berthing ships at a port and unloading the stowed materials require a series of scheduling problems: ship berthing, discharging, and material transport. To deal effectively with the scheduling complexity due to mutual interdependence among those problems, this paper proposes a two-level hierarchical architecture for the integrated scheduling of all the activities arising in port. The hierarchical architecture assigns ships to multiple lower level dispatchers, each of which makes its own discharging and material transport schedule independently while satisfying the requirements imposed by the higher level coordinator. If any problem occurs within a dispatcher, the higher level coordinator attempts to resolve the trouble through the coordination of other dispatchers. Based on the hierarchical architecture, a prototype scheduling expert system is developed using G2 for the port scheduling problem at a steelworks. Through the object- oriented interaction of frames, the system is shown to effectively construct integrated schedules from the berth scheduling to the material transport scheduling.
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    ESAS: A case-based approach to business planning and monitoring (1998)
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    Notes: Abstract: Creating and sustaining a competitive advantage in today’s turbulent world markets is a formidable business challenge. For many organisations, operating within an inherently unstable external environment has resulted in the need for a cultural rethink. Business complacency, brought about by corporate industry monopolisation, the reliance on reputation, brand identity, and customer allegiance, is no longer a recipe for sustained market growth. Companies have realised that being market focused could provide them with a competitive edge within the marketplace. To achieve this organisations have turned to the ‘Quality movement’, embracing the Total Quality Management (TQM) philosophy and its inherent tools (auditing frameworks, concept of quality systems etc.) as a means to recapture lost ground. ESAS (Enterprise Strategic Advisory System) is a prototype intelligent system that utilises a case- based approach to address the issues raised above, by providing organisations with advice on market- led quality and competitive strategy. This paper explores the philosophy and ideas behind the ESAS concept, and describes the development of an ESAS prototype.
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    The Two Faces of AI: AAAI ’97 - Providence, Rhode Island, USA, 27–31 July 1997 (1998)
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    Book Reviews (1998)
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    Notes: Gillies, Donald, Artificial Intelligence and Scientific MethodGurney, Kevin, An Introduction to Neural Networks
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    Towards Industrial Application of Intelligent Training Systems (1998)
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    Notes: Computer-based training is an area where knowledge-based techniques enable us to achieve new system functionalities which cannot be attained with conventional techniques. Knowledge-based training systems can adapt the course, the lesson and the instructional strategy to the needs and attitude of the individual trainee, so as to obtain a completely individualised instruction. Due to these capabilities they are known as Intelligent Training Systems (ITSs). After their introduction in the mid-eighties with their first successful application in the military sector, ITSs are now mature enough for practical use in civil applications.This paper presents the experience gained by the authors over the last decade through the realisation of two industrial prototypes in different sectors and the recent development of a full-scale application. Such experience led to a specification methodology and to a development framework which now provide a solid baseline for the industrial application of the ITS technology.
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    Truth Maintenance in Blackboard Environment (1998)
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    Notes: Constraint satisfaction and search problems generally fall into the class of problems for which a direct algorithmic solution does not exist. The solution of these problems requires the examination of state spaces. A problem solver (inference engine) alone is not able to organize and maintain state space consistently. For this purpose a so-called truth maintenance system is required. Our truth maintenance system (MEKON) organizes data within a data abstraction called a context. Each context corresponds to one problem state and contains currently believed data. The truth maintenance system provides believed data retrieval, belief revision, contradiction handling and non-monotonicity handling, the features that help a problem solver to examine state spaces. MEKON represents an ATMS-like system implemented within BEST (Blackboard-based Expert System Toolkit). However, some special MEKON features such as state variables, context sensitive generation of assumptions and explicit context generation, that are not present in standard ATMSs, facilitate not only the solution of constraint satisfaction problems, but also the solution of search problems (not provided by standard ATMSs). Being deeply integrated with Prolog/Rex, BEST’s knowledge representation language, and BEST’s inference engine, MEKON provides a simple and efficient means for the examination of state spaces. Facts, hypotheses (assumptions), and concepts (frames) are used to describe a problem state, contexts are used to represent points in the state spaces, while rules are used to perform state transitions. MEKON is the only truth maintenacne system that provides truth maintenance capabilities on local blackboards thus enabling the solution of complex problems which include different kinds of real constraint satisfaction and search problems concerning diagnosis, allocation tasks, classification tasks, planning or scenario making.
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    Book Reviews (1997)
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    Notes: Russell, Stuart and Norvig, Peter Artificial Intelligence: A Modern ApproachEdwards, Alistair, D.N. (ed.) Extra-Ordinary Human-Computer Interaction: Interfaces for Users with DisabilitiesVacca, John R. VRML: Bringing Virtual Reality to the Internet
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    REDSIEX: A Cooperative Network of Expert Systems with Blackboard Architectures (1997)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 14 (1997), S. 0 
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    Source: Blackwell Publishing Journal Backfiles 1879-2005
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    Notes: The blackboard architecture, originally developed for the system that permits the comprehension of language, HEARSAY II, has later been used in a great variety of domains and in various environments for the construction of systems. From the classic architecture of HEARSAY II, many applications, generalizations, extensions and refinements have been developed. In this paper we present REDSIEX, (RED de SIstemas EXpertos) which is a network of expert systems within a blackboard architecture, for the cooperation solution of distributed problems. The REDSIEX system inherits various of the elements defined by the architecture of HEARSAY II and incorporates new components and organization. These produce a very characteristic and exclusive global work style in the solution of problems, within a conceptual framework of emergent control. The main structural and functional characteristics of REDSIEX are discussed.
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    Diary (1997)
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    An Intelligent Business Advisor System for Stock Investment (1997)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 14 (1997), S. 0 
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    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: This paper presents an intelligent system to assist small investors to determine stock trend signals for investment in stock business. A pilot system is built providing three main categories of technical and analysis theories, namely momentum, moving average, and support/resistance line. It has extensive graphic interface design to facilitate the usage of the system. For novice investors, the system is associated with tutoring features and it supports analysis study of the rationale behind some system recommendations. Skilful investors can explore the various theories for the prediction by means of adjusting the weightings, combinations and even some independent variables allocated by the intelligent system. General users can therefore formulate their investment strategies upon system recommendations under different investment criteria accordingly.
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    Using the CARMEN’s framework to model and acquire knowledge (1997)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 14 (1997), S. 0 
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    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: The manner in which CARMEN (Constraints And Rules Management ENgine), an operational expert system generator developed as part of the ESPRIT project ITHACA, models and acquires knowledge is discussed. Central to CARMEN are three types of control entities (TASKs, MKSs and BKSs) which are used to describe problem-solving at the knowledge-use level. Modeling of domain knowledge is done both at the deep and surface levels. The Integrity Checking Task (or ICT) is used to illustrate the manner in which CARMEN works. We conclude the paper with a comparison of CARMEN with other approaches in knowledge modeling.
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    The analysis and performance evaluation of the pheromone-Q-learning algorithm (2004)
    Oxford, UK : Blackwell Publishing
    Expert systems 21 (2004), S. 0 
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    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: The paper presents the pheromone-Q-learning (Phe-Q) algorithm, a variation of Q-learning. The technique was developed to allow agents to communicate and jointly learn to solve a problem. Phe-Q learning combines the standard Q-learning technique with a synthetic pheromone that acts as a communication medium speeding up the learning process of cooperating agents. The Phe-Q update equation includes a belief factor that reflects the confidence an agent has in the pheromone (the communication medium) deposited in the environment by other agents. With the Phe-Q update equation, the speed of convergence towards an optimal solution depends on a number of parameters including the number of agents solving a problem, the amount of pheromone deposit, the diffusion into neighbouring cells and the evaporation rate. The main objective of this paper is to describe and evaluate the performance of the Phe-Q algorithm. The paper demonstrates the improved performance of cooperating Phe-Q agents over non-cooperating agents. The paper also shows how Phe-Q learning can be improved by optimizing all the parameters that control the use of the synthetic pheromone.
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    The application of a fuzzy-rule-based system in an exposition of the antecedents of sedge warbler song flight (2004)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
    Expert systems 21 (2004), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract:  The utilization of a fuzzy aspect within data analysis attempts to move from a quantitative to a more qualitative investigative environment. As such, this may allow the more non-quantitative researchers results they can use, based on sets of linguistic terms. In this paper an inductive fuzzy decision tree approach is utilized to construct a fuzzy-rule-based system for the first time in a biological setting. The specific biological problem considered attempts to identify the antecedents (conditions in the fuzzy decision rules) which characterize the length of song flight of the male sedge warbler when attempting to attract a mate. Hence, for a non-quantitative investigator the resultant set of fuzzy rules allows an insight into the linguistic interpretation on the relationship between associated characteristics and the respective song flight duration.
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    Categorial expert systems (2004)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
    Expert systems 21 (2004), S. 0 
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    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: Expert systems can be used to determine some objects or consequences from uncertain knowledge by hierarchical categorization. Categorical representation is psychologically motivated and also offers an explanation of how to deal with uncertain knowledge based on counting during approximate reasoning. It is an alternative to other well-known uncertainty calculi. A knowledge base which is used during approximate reasoning is represented by a taxonomical arrangement of verbal categories. Priming eases the formation of the final hypothesis, as more exact possible hypotheses are formed. The approximate reasoning is demonstrated on an expert system ‘Jurassic’ from the field of paleontology for the determination of a dinosaur species. It helps the paleontologist to determine creatures from uncertain knowledge. The system is composed of 423 rules arranged in a directed acyclic graph with a depth of 5. This knowledge is represented by a taxonomical arrangement of verbal categories represented by associative memories.
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    News (2004)
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    CRAS-CBR: Internal control risk assessment system using case-based reasoning (2004)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
    Expert systems 21 (2004), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: Information technology and the Internet have been major drivers for changes in all aspects of business processes and activities. They have brought major changes to the financial statements audit environment as well, which in turn has required modifications in audit procedures. There exist certain difficulties, however, with current audit procedures especially for the assessment of the level of control risk. This assessment is primarily based on the auditors' professional judgment and experiences, not on objective rules or criteria.To overcome these difficulties, we propose a prototype decision support model named CRAS-CBR using case-based reasoning to support auditors in making their professional judgment on the assessment of the level of control risk of the general accounting system in the manufacturing industry.To validate the performance, we compare our proposed model with benchmark performances in terms of classification accuracy for the level of control risk. Our experimental results show that CRAS-CBR outperforms a statistical model and staff auditor performance in average hit ratio.
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    Knowledge acquisition in incomplete fuzzy information systems via the rough set approach (2003)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
    Expert systems 20 (2003), S. 0 
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    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: Machine learning can extract desired knowledge from training examples and ease the development bottleneck in building expert systems. Most learning approaches derive rules from complete and incomplete data sets. If attribute values are known as possibility distributions on the domain of the attributes, the system is called an incomplete fuzzy information system. Learning from incomplete fuzzy data sets is usually more difficult than learning from complete data sets and incomplete data sets. In this paper, we deal with the problem of producing a set of certain and possible rules from incomplete fuzzy data sets based on rough sets. The notions of lower and upper generalized fuzzy rough approximations are introduced. By using the fuzzy rough upper approximation operator, we transform each fuzzy subset of the domain of every attribute in an incomplete fuzzy information system into a fuzzy subset of the universe, from which fuzzy similarity neighbourhoods of objects in the system are derived. The fuzzy lower and upper approximations for any subset of the universe are then calculated and the knowledge hidden in the information system is unravelled and expressed in the form of decision rules.
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    Probabilistic approaches to rough sets (2003)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
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    Notes: Abstract: Probabilistic approaches to rough sets in granulation, approximation and rule induction are reviewed. The Shannon entropy function is used to quantitatively characterize partitions of a universe. Both algebraic and probabilistic rough set approximations are studied. The probabilistic approximations are defined in a decision-theoretic framework. The problem of rule induction, a major application of rough set theory, is studied in probabilistic and information-theoretic terms. Two types of rules are analyzed: the local, low order rules, and the global, high order rules.
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    A rough set approach to knowledge reduction based on inclusion degree and evidence reasoning theory (2003)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
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    Notes: Abstract: The theory of rough sets is an extension of set theory for studying intelligent systems characterized by insufficient and incomplete information. We discuss the basic concept and properties of knowledge reduction based on inclusion degree and evidence reasoning theory, and propose a knowledge discovery approach based on inclusion degree and evidence reasoning theory.
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    Acquisition of hierarchy-structured probabilistic decision tables and rules from data (2003)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
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    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: The paper is concerned with the creation of predictive models from data within the framework of the variable precision rough set model. It is focused on two aspects of the model derivation: computation of uncertain, in general, rules from information contained in probabilistic decision tables and forming hierarchies of decision tables with the objective of reduction or elimination of decision boundaries in the resulting classifiers. A new technique of creation of a linearly structured hierarchy of decision tables is introduced and compared to tree-structured hierarchy. It is argued that the linearly structured hierarchy has significant advantages over tree-structured hierarchy.
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    News (2003)
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    Diary (2003)
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    A variational approach to intensity approximation for remote sensing images using dynamic neural networks (2003)
    Oxford, UK : Blackwell Publishing
    Expert systems 20 (2003), S. 0 
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    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Abstract: In remote sensing image processing, image approximation, or obtaining a high-resolution image from a corresponding low-resolution image, is an ill-posed inverse problem. In this paper, the regularization method is used to convert the image approximation problem into a solvable variational problem. In regularization, the constraints on smoothness and discontinuity are considered, and the original ill-posed problem is thereby converted to a well-posed optimization problem. In order to solve the variational problem, a Hopfield-type dynamic neural network is developed. This neural network possesses two states that describe the discrepancy between a pixel and adjacent pixels, the intensity evolution of a pixel and two kinds of corresponding weights. Based on the experiment in this study with a Landsat TM image free of added noise and a noisy image, the proposed approach provides better results than other methods. The comparison shows the feasibility of the proposed approach.
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    A knowledge processing method for intelligent systems based on inclusion degree (2003)
    Oxford, UK : Blackwell Publishing
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    Notes: The probability reasoning method, fuzzy reasoning method, evidential reasoning method and other reasoning methods are main techniques employed in intelligent systems for processing uncertain and vague information. The concept of inclusion degree was proposed earlier and it has been proved that the methods mentioned above are examples of inclusion degrees. In this paper, we introduce type S1 and type S2 inclusion degrees, discuss the relationship between them, and further propose inclusion degrees on interval numbers, divisions, vectors and set vectors. This paper addresses an uncertainty analysis method with different inclusion degrees for intelligent systems and other systems such as fuzzy relational databases.
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    An intelligent agent with layered architecture for operating systems resource management (2003)
    Oxford, UK : Blackwell Publishing
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    Notes: Abstract: A software agent is defined as an autonomous software entity that is able to interact with its environment. Such an agent is able to respond to other agents and/or its environment to some degree, and has some sort of control over its internal state and actions. In belief–desire–intention (BDI) theory, an agent's behavior is described in terms of a processing cycle. In this paper, based on BDI theory, the processing cycle is studied with a software feedback mechanism. A software feedback or loop-back control mechanism can perform functions without direct external intervention. A feedback mechanism can continuously monitor the output of the system under control (the target system), compare the result against preset values (goals of the feedback control) and feed the difference back to adjust the behavior of the target system in a processing cycle. We discuss the modeling and design aspects of an autonomous, adaptive monitoring agent with layered control architecture. The architecture consists of three layers: a scheduling layer, an optimizing layer and a regulating layer. Experimental results show that the monitoring agent developed for an e-mail server is effective.
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    A new and efficient ant-based heuristic method for solving the traveling salesman problem (2003)
    Oxford, UK : Blackwell Publishing
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    Notes: Abstract: In this paper, we present an efficient metaheuristic approach for solving the problem of the traveling salesman. We introduce the multiple ant clans concept from parallel genetic algorithms to search solution space using different islands to avoid local minima in order to obtain a global minimum for solving the traveling salesman problem. Our simulation results indicate that the proposed novel traveling salesman problem method (called the ACOMAC algorithm) performs better than a promising approach named the ant colony system. This investigation is concerned with a real life logistics system design which optimizes the performance of a logistics system subject to a required service level in the vehicle routing problem. In this work, we also concentrate on developing a vehicle routing model by improving the ant colony system and using the multiple ant clans concept. The simulation results reveal that the proposed method is very effective and potentially useful in solving vehicle routing problems.
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    Diary (2003)
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    A model of a decision support system based on case-based reasoning for third-party logistics evaluation (2003)
    Oxford, UK : Blackwell Publishing
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    Notes: The social demands for third-party logistics (3PL) are further developing the model of supply chain management. The analysis of an effective approach for 3PL service supplier evaluation is given in terms of its direct relation to the operational efficiency and benefit of the service-demanding enterprise as well as its supply chain management. An analysis of the traditional academic theoretical results and practical methods for 3PL supplier selection indicates the deficiencies of this approach. In this paper, a case-based reasoning model framework is postulated for a 3PL evaluation and selection system. This work further expands upon the theoretical basis of this system and its reasoning process by discussing the advantages and practical value of this framework.
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    On a responsive replenishment system: a fuzzy logic approach (2003)
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    Notes: In today's competitive business environment, it is important that customers are able to obtain their preferred items in the shops they visit, particularly for convenience store chains such as 7–Eleven where popular items are expected to be readily available on the shelves of the stores for buyers. To minimize the cost of running such store chains, it is essential that stocks be kept to a minimum and at the same time large varieties of popular items are available for customers. In this respect, the replenishment system needs to be able to cope with the taxing demands of minimal inventory but at the same time keeping large varieties of needed items. This paper proposes a replenishment system which is able to respond to the fluctuating demands of customers and provide a timely supply of needed items in a cost–effective way. The proposed system embraces the principle of fuzzy logic which is able to deal with uncertainties by virtue of its fuzzy rules reasoning mechanism, thereby leveraging the responsiveness of the entire replenishment system for the chain stores. To validate the feasibility of the approach, a case study has been conducted in an emulated environment with promising results.
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    Providing Websites with capabilities of one–to–one marketing (2003)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
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    Notes: A formidable synergy can be obtained by putting expert system technology into the Internet. The modern trend of embedding expert systems into Websites turns out to be very promising, in particular for the field of marketing via the Web. The last two years have seen a growing interest in providing Websites with suitable embedded expert systems for one–to–one marketing. One–to– one marketing means marketing in a personalized way, i.e. marketing in a way that is adaptive to the personal needs of the user. A basic feature of this marketing framework consists in personalized prioritizing of news, i.e. presenting information in an order that is relevant to the specific needs of the current user. If the personalized prioritizing of news is a very useful feature in wired Web, it becomes essential in wireless Web, the promising next generation of the Web.The paper presents a general methodology for personalized prioritizing of news. The methodology integrates decision theory with a deep–knowledge–based user model (i.e. causal knowledge linking user preferences to user goals). The deep–knowledge model of the user is a source of power of the methodology because it allows the system to know (and possibly explain) why the user acts the way he/she acts. Another relevant aspect of the methodology is that the burden of personalization is not placed on the user, and in fact the user does not have to declare his/her needs or interests or goals: they are automatically inferred from his/her profile data. In order to investigate the ideas underlying the proposal, a methodology example has been implemented in a prototype and then tested on real cases in the context of a supercomputing portal.
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    The perverse horrors of user–centric design (2002)
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    Notes: The usefulness of ‘user centred design’ as a concept in the design of software systems is considered. It is concluded that the concept is frequently used in a way so vacuous as to be devoid of meaning, and would be better discarded. Some suggestions are made for further research in this area; some modest suggestions are also offered to those who wish to develop systems of a type better suited to the needs of civilized society.
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    Chaotic analysis of predictability versus knowledge discovery techniques: case study of the Polish stock market (2002)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
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    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Increasing evidence over the past decade indicates that financial markets exhibit nonlinear dynamics in the form of chaotic behavior. Traditionally, the prediction of stock markets has relied on statistical methods including multivariate statistical methods, autoregressive integrated moving average models and autoregressive conditional heteroskedasticity models. In recent years, neural networks and other knowledge techniques have been applied extensively to the task of predicting financial variables.This paper examines the relationship between chaotic models and learning techniques. In particular, chaotic analysis indicates the upper limits of predictability for a time series. The learning techniques involve neural networks and case–based reasoning. The chaotic models take the form of R/S analysis to measure persistence in a time series, the correlation dimension to encapsulate system complexity, and Lyapunov exponents to indicate predictive horizons. The concepts are illustrated in the context of a major emerging market, namely the Polish stock market.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00213
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    A prototype store choice and location modelling system using Dempster–Shafer theory (2002)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 19 (2002), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: This paper concerns the study of destination choice modelling, more specifically identifying within some area (e.g. a city) the region where a particular store is the most favourable to be visited by individuals. An influence measure is constructed for each individual, which incorporates the modern technique known as Dempster–Shafer theory. Based on the evidence of the shopping destinations of individuals, geographical regions are found for levels of largest belief and plausibility (within Dempster–Shafer theory) for specific stores being the most favourable to visit. Additionally, this method may be used to identify the possible position of new stores, based on regions of most uncertainty or conflict in store choice. A prototype choice modelling system is introduced to enable the series of associated results to be easily visualized and analysed.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00214
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  • 90
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    Diary (2002)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 19 (2002), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00211
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  • 91
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    Monitoring the supply of products in a supply chain environment: a fuzzy neural approach (2002)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 19 (2002), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Fuzzy logic principles and neural networks, both being computational intelligence technologies, can be combined to produce synergetic effects through the formation of a unified approach which takes advantage of the benefits and at the same time counterbalances the flaws of the two technologies. In this paper, a fuzzy neural approach, which is characterized by its ability to suggest the appropriate adjustment of product quantity from various suppliers with different quality standards in a supply chain network, is presented. This approach is particularly useful in situations where multiple supply chain partners are involved to achieve the common objective of producing products to the best satisfaction of customer demands at the lowest possible cost. To validate the feasibility of this approach, a test has been conducted based on the proposed fuzzy neural approach with the objective of suggesting the appropriate selection of suppliers and the optimal quantity allocated to them to meet the required quality standards. This paper describes the methodology for the deployment of this proposed hybrid approach to enhance the machine intelligence of a supply chain network with the description of a case study to exemplify its underlying principles.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00208
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  • 92
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    News (2002)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 19 (2002), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00201
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  • 93
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    Development of an Intelligent Data-Mining System for a Dispersed Manufacturing Network (2001)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 18 (2001), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Recent advances related to on-line analytical processing (OLAP) have resulted in a significant improvement in data analysis efficiency by virtue of its multidimensional database structure and pre-computing operations of measuring data. However, the research related to the design and implementation of OLAP, particularly in the support of dispersed manufacturing networks in terms of ‘intelligent decision making’, has yet to be considered as remarkable. Research studies indicate that the level of intelligence of decision support systems can be enhanced with the incorporation of computational intelligence techniques such as case-based reasoning or rule-based reasoning. This paper describes the development of an intelligent data-mining system using a rule-based OLAP approach which can be adopted to support dispersed manufacturing networks in terms of performance enhancement. In this paper, the techniques, methods and infrastructure for the development of such a data-mining system, which possesses certain intelligent features, are presented. To validate the feasibility of this approach, a case example related to the testing of the approach in an emulated industrial environment is covered.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00172
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    An Efficient Expert System for Air Compressor Troubleshooting (2001)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 18 (2001), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: In this paper, an expert system for automobile air compressor troubleshooting (ACTS) is presented. This system can assist users to conduct an efficient and effective diagnosis on air compressor failures. Unlike most diagnosis expert systems, ACTS uses a new control strategy to enhance the efficiency of the diagnostic process. This control strategy attempts to spend the least amount of time to detect the compressor fault accurately by investigating only portions of the knowledge base. ACTS first constructs a diagnostic tree based on the functions or connectivity of the air compressor's devices. A fuzzy multiple-attribute decision-making method is used to determine the priority of the nodes (devices) in the diagnostic tree. The prioritized result creates a ‘meta knowledge base’ to control the diagnostic process. In addition, each node possesses its own knowledge base for hypothesizing the possible faults for the node. ACTS, written in MS Visual BASIC, has been successfully developed and implemented in MS-Windows environment on a PC. To validate the system performance, ACTS is compared to EXACT, an expert system for automobile air compressor troubleshooting, using 50 sample cases. The evaluation results indicate that ACTS performs better than EXACT by reducing the number of queries and the diagnosis time by 20.7% and 24.9%, respectively.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00175
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  • 95
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    Editorial (2001)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 18 (2001), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00035-i3
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  • 96
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    News (2001)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 18 (2001), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00168
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    Development of an Expert System Shell Based on Genetic Algorithms for the Selection of the Energy Best Available Technologies and their Optimal Operating Conditions for the Process Industry (2001)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 18 (2001), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: The development of genetic algorithms started almost three decades ago in an attempt to imitate the mechanics of natural systems. Since their inception, they have been applied successfully as optimization methods, and as expert systems, in many diverse applications. In this paper, a genetic-algorithm-based expert system shell is presented that, when combined with a proper database comprising the available energy-saving technologies for the process industry, is able to perform the following tasks: (a) identify the best available technologies (BATs) among the available ones for a given process industry, and (b) calculate their optimal design parameters in such a way that they comply with the energy requirements of the process. By the term BAT is meant the available energy-saving technology, among the existing ones in the market, that is the best for the case.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00165
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    A Model-Based Method for an Online Diagnostic Knowledge-Based System (2001)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 18 (2001), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: Fault diagnosis is very important for modern production technology and has received increasing theoretical and practical attention during the last few years. This paper presents a model-based diagnostic method for industrial systems. An online, real-time, deep knowledge based fault detection system has been developed by combining different development environments and tools. The system diagnoses, predicts and compensates faults by coupling symbolic and numerical data in a new environment suitable for the interaction of different sources of knowledge and has been successfully implemented and tested on a real hydraulic system.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00167
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    The Dialoguer: An Interactive Bilingual Interface to a Network Operating System (2001)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 18 (2001), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Notes: We have developed a bilingual interface to the Novell network operating system, called the Dialoguer. This system carries on a conversation with the user in Arabic or English or a combination of the two and attempts to help the user use the Novell network operating system. Learning to use an operating system is a major barrier in starting to use computers. There is no single standard for operating systems which makes it difficult for novice users to learn a new operating system. With the proliferation of client–server environments, users will eventually end up using one network operating system or another. These problems motivated our choice of an area to work in and they have made it easy to find real users to test our system.This system is both an expert system and a natural language interface. The system embodies expert knowledge of the operating system commands and of a large variety of plans that the user may want to carry out. The system also contains a natural language understanding component and a response generation component. The Dialoguer makes extensive use of case frame tables in both components. Algorithms for handling a bilingual dialogue are one of the important contributions of this paper along with the Arabic case frames.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00166
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    Diary (2001)
    Oxford, UK and Boston, USA : Blackwell Publishers Ltd
    Expert systems 18 (2001), S. 0 
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    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00169
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