Sinossi
Great progresses have been made in the application of fuzzy set theory and fuzzy logic. Most remarkable area of application is 'fuzzy control', where fuzzy logic was first applied to plant control systems and its use is expanding to consumer products. Most of fuzzy control systems uses fuzzy inference with max-min or max-product composition, similar to the algorithm that first used by Mamdani in 1970s. Some algorithms are developed to refine fuzzy controls systems but the main part of algorithm stays the same. Triggered by the success of fuzzy control systems, other ways of applying fuzzy set theory are also investigated. They are usually referred to as 'fuzzy expert sys tems', and their purpose are to combine the idea of fuzzy theory with AI based approach toward knowledge processing. These approaches can be more generally viewed as 'fuzzy information processing', that is to bring fuzzy idea into informa tion processing systems.
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Contenuti
Preface. Part 1: General Issues. 1. Fuzzy Sets and Fuzzy Reasoning: an Introduction; S.G. Tzafestas, A.N. Venetsanopoulos, S. Terzakis. 2. On the Validation of Fuzzy Knowledge Bases; D. Dubois, H. Prade. 3. Software Representation of Fuzzy Sets and Logic; S. Yamamoto. 4. Fuzzy Dynamic Systems: Analysis, Control, and Identification; A.N. Venetsanopoulos, S.G. Tzafestas, S. Terzakis. Part 2: Neuro-Fuzzy Systems. 5. Neural Net Applications in Fuzzy Systems; KappaH. Kawamura, A.kappa KappaTani.kappa 6. Neuro-Fuzzy Expert Systems: Overview with a Case Study; S. Mitra, S.P. Pal. 7. Fuzzy Reasoning through a General Neural Network Model; S.G. Tzafestas, G.B. Stamou, K. Watanabe. Part 3: Fuzzy Controllers. 8. Demystification of Fuzzy Control; R. Jager, H.B. Verbruggen, P.M. Bruijn. 9. Analysis, Design, Implementation and Critical Appreciation of Fuzzy Logic Controller; K.S. Ray. 10. Fuzzy Controller Design: a Sliding Mode Approach; C.-C. Kung, S.-C. Lin. 11. Multivariable Fuzzy Sliding Mode Control by Using a Simplex of Control Vectors; G. Bartolini, A. Ferrara. 12. Knowledge Representation and Information Processing in Intelligent Controllers; K. Hirota, W. Pedrycz. Part 4: Fuzzy Reasoning and Estimation Methodologies. 13. Fuzzy Parameter and State Estimation; S.G. Tzafestas, S. Terzakis, A.N. Venetsanopoulos. 14. A Fuzzy Reasoning Methodology for Rule-Based Systems; S.-M. Chen. 15. Computing the Multivariate Shape of a Pattern Class in Rn; D.P. Mandal, C.A. Murthy. Part 5: Applications. 16. Robotic Control Using Fuzzy Logic and Parallel Processing; M.I. Henderson, K.F. Gill. 17. Fuzzy Control of Robotic Manipulators and Mechanical Systems; R. Gorez, M. De Neyer. 18. Fuzzy Control for Robot Manipulators with Artificial Rubber Muscles; K. Watanabe, S. Jin, S.G. Tzafestas. 19. Fuzzy Petri Nets and Applications; C. Looney. 20. Fuzzy Logic-Based Tools for the Acquisition and Representation of Knowledge in Biomedical Applications; E. Binaghi. 21. Fuzzy Logic Design of a Non-Destructive Robotic Fruit Collector; S.G. Tzafestas, F.V. Hatzivasiliou, S.K. Kaltsounis. Subject Index.
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Great progresses have been made in the application of fuzzy set theory and fuzzy logic. Most remarkable area of application is fuzzy control , where fuzzy logic was first applied to plant control systems and its use is expanding to consumer products. Most . Codice articolo 5837181
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Paperback. Condizione: new. Paperback. Great progresses have been made in the application of fuzzy set theory and fuzzy logic. Most remarkable area of application is 'fuzzy control', where fuzzy logic was first applied to plant control systems and its use is expanding to consumer products. Most of fuzzy control systems uses fuzzy inference with max-min or max-product composition, similar to the algorithm that first used by Mamdani in 1970s. Some algorithms are developed to refine fuzzy controls systems but the main part of algorithm stays the same. Triggered by the success of fuzzy control systems, other ways of applying fuzzy set theory are also investigated. They are usually referred to as 'fuzzy expert sys tems', and their purpose are to combine the idea of fuzzy theory with AI based approach toward knowledge processing. These approaches can be more generally viewed as 'fuzzy information processing', that is to bring fuzzy idea into informa tion processing systems. Great progresses have been made in the application of fuzzy set theory and fuzzy logic. Most of fuzzy control systems uses fuzzy inference with max-min or max-product composition, similar to the algorithm that first used by Mamdani in 1970s. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9789401740821
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Great progresses have been made in the application of fuzzy set theory and fuzzy logic. Most remarkable area of application is 'fuzzy control', where fuzzy logic was first applied to plant control systems and its use is expanding to consumer products. Most of fuzzy control systems uses fuzzy inference with max-min or max-product composition, similar to the algorithm that first used by Mamdani in 1970s. Some algorithms are developed to refine fuzzy controls systems but the main part of algorithm stays the same. Triggered by the success of fuzzy control systems, other ways of applying fuzzy set theory are also investigated. They are usually referred to as 'fuzzy expert sys tems', and their purpose are to combine the idea of fuzzy theory with AI based approach toward knowledge processing. These approaches can be more generally viewed as 'fuzzy information processing', that is to bring fuzzy idea into informa tion processing systems. 592 pp. Englisch. Codice articolo 9789401740821
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Taschenbuch. Condizione: Neu. Fuzzy Reasoning in Information, Decision and Control Systems | S. G. Tzafestas (u. a.) | Taschenbuch | xx | Englisch | 2013 | Springer | EAN 9789401740821 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. Codice articolo 105650299
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Great progresses have been made in the application of fuzzy set theory and fuzzy logic. Most remarkable area of application is 'fuzzy control', where fuzzy logic was first applied to plant control systems and its use is expanding to consumer products. Most of fuzzy control systems uses fuzzy inference with max-min or max-product composition, similar to the algorithm that first used by Mamdani in 1970s. Some algorithms are developed to refine fuzzy controls systems but the main part of algorithm stays the same. Triggered by the success of fuzzy control systems, other ways of applying fuzzy set theory are also investigated. They are usually referred to as 'fuzzy expert sys tems', and their purpose are to combine the idea of fuzzy theory with AI based approach toward knowledge processing. These approaches can be more generally viewed as 'fuzzy information processing', that is to bring fuzzy idea into informa tion processing systems.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 592 pp. Englisch. Codice articolo 9789401740821
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