Synopsis
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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Fuzzy Reasoning in Information, Decision and Control Systems (Intelligent Systems, Control and Automation: Science and Engineering, 11)
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Springer, 1994
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Fuzzy Reasoning in Information, Decision and Control Systems (Intelligent Systems, Control and Automation: Science and Engineering, 11)
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Fuzzy Reasoning in Information, Decision and Control Systems
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Springer Netherlands, 1994
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Gebunden. Etat : New. 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 . N° de réf. du vendeur 5966996
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Fuzzy Reasoning in Information, Decision and Control Systems
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Kluwer Academic Publishers, 1994
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Etat : New. Devoted to the study of fuzzy reasoning as applied to decision making and control processes. This book contains a collection of contributions covering a range of topics within the field. It is suitable for the researcher and practitioner, as well as for the teacher and student in related Master and Doctoral courses. Editor(s): Tzafestas, Spyros G.; Venetsanopoulos, A. N. Series: Intelligent Systems, Control and Automation: Science and Engineering. Num Pages: 588 pages, biography. BIC Classification: TJFM. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 240 x 152 x 33. Weight in Grams: 1006. . 1994. Hardback. . . . . N° de réf. du vendeur V9780792326434
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Fuzzy Reasoning in Information, Decision and Control Systems
Edité par
Kluwer Academic Publishers, 1994
ISBN 10 : 0792326431
ISBN 13 : 9780792326434
Neuf
Couverture rigide
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Etat : New. Devoted to the study of fuzzy reasoning as applied to decision making and control processes. This book contains a collection of contributions covering a range of topics within the field. It is suitable for the researcher and practitioner, as well as for the teacher and student in related Master and Doctoral courses. Editor(s): Tzafestas, Spyros G.; Venetsanopoulos, A. N. Series: Intelligent Systems, Control and Automation: Science and Engineering. Num Pages: 588 pages, biography. BIC Classification: TJFM. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 240 x 152 x 33. Weight in Grams: 1006. . 1994. Hardback. . . . . Books ship from the US and Ireland. N° de réf. du vendeur V9780792326434
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Fuzzy Reasoning in Information, Decision and Control Systems (Intelligent Systems, Control and Automation: Science and Engineering (11))
Edité par
Springer, 1994
ISBN 10 : 0792326431
ISBN 13 : 9780792326434
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Fuzzy Reasoning in Information, Decision and Control Systems
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Springer Feb 1994, 1994
ISBN 10 : 0792326431
ISBN 13 : 9780792326434
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Buch. Etat : Neu. 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. N° de réf. du vendeur 9780792326434
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