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  • Articles  (493,335)
  • 2010-2014  (376,986)
  • 1995-1999  (116,349)
  • Natural Sciences in General  (404,704)
  • Computer Science  (146,859)
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  • Books  (73)
  • Articles  (493,335)
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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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    Paper (German National Licenses)
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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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    Paper (German National Licenses)
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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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    Paper (German National Licenses)
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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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    Paper (German National Licenses)
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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
    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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  • 8
    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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  • 9
    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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  • 10
    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 
    Details
    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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    Paper (German National Licenses)
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