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  • Articles  (31)
  • American Meteorological Society
  • Blackwell Publishing Ltd
  • Springer Nature
  • Springer Science + Business Media
  • 2000-2004  (31)
  • 1960-1964
  • Computer Science  (22)
  • Philosophy  (9)
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  • Articles  (31)
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  • 1
    Electronic Resource
    Electronic Resource
    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 
    Details
    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.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1468-0394.2004.00258.x
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  • 2
    Electronic Resource
    Electronic Resource
    Categorial expert systems (2004)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
    Expert systems 21 (2004), S. 0 
    Details
    ISSN: 1468-0394
    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.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1468-0394.2004.00261.x
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  • 3
    Electronic Resource
    Electronic Resource
    News (2004)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
    Expert systems 21 (2004), 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/j.1468-0394.2004.00262.x
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  • 4
    Electronic Resource
    Electronic Resource
    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 
    Details
    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.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1468-0394.2004.00260.x
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  • 5
    Electronic Resource
    Electronic Resource
    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 
    Details
    ISSN: 1468-0394
    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.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00252
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  • 6
    Electronic Resource
    Electronic Resource
    Probabilistic approaches to rough sets (2003)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
    Expert systems 20 (2003), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    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.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00253
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  • 7
    Electronic Resource
    Electronic Resource
    A rough set approach to knowledge reduction based on inclusion degree and evidence reasoning theory (2003)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
    Expert systems 20 (2003), S. 0 
    Details
    ISSN: 1468-0394
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    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.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00254
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  • 8
    Electronic Resource
    Electronic Resource
    Acquisition of hierarchy-structured probabilistic decision tables and rules from data (2003)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
    Expert systems 20 (2003), S. 0 
    Details
    ISSN: 1468-0394
    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.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/1468-0394.00255
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  • 9
    Electronic Resource
    Electronic Resource
    News (2003)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
    Expert systems 20 (2003), 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/10.1111/1468-0394.00256
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  • 10
    Electronic Resource
    Electronic Resource
    Diary (2003)
    Oxford, UK and Boston, USA : Blackwell Publishing Ltd
    Expert systems 20 (2003), 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/10.1111/1468-0394.00257
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