Fuzzy Reasoning in Information, Decision and Control Systems

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S.G. Tzafestas, Anastasios N. Venetsanopoulos
Springer Netherlands, Feb 28, 1994 - Technology & Engineering - 568 pages
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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Contents

CHAPTER
3
Generalization of the Three Fundamental Operations
11
Some Basic Theorems and Principles
17
Copyright

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About the author (1994)

Tzafestas is Professor of Control and Automation at the National Technical University, Athens, Greece.

Anastasios Venetsanopoulos is a Professor of Electrical and Computer Engineering at Ryerson University in Toronto, Ontario, and a Professor Emeritus with the Edward S. Rogers Department of Electrical and Computer Engineering at the University of Toronto. He has authored eight books, contributed chapters to thirty books and published over 830 technical papers. He is a Fellow of the Engineering Institute of Canada, the IEEE, the Canadian Academy of Engineering and the Royal Society of Canada.

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