Fuzzy Reasoning in Information, Decision and Control Systems


Table of contents

  1. Front Matter
    Pages I-xviii
  2. General Issues

    1. Front Matter
      Pages 1-1
    2. S. G. Tzafestas, A. N. Venetsanopoulos, S. Terzakis
      Pages 3-29
    3. Didier Dubois, Henri Prade
      Pages 31-49
    4. A. N. Venetsanopoulos, S. G. Tzafestas, S. Terzakis
      Pages 69-96
  3. Neuro-Fuzzy Systems

    1. Front Matter
      Pages 97-97
    2. Hiroshi Kawamura, Akinori Tani
      Pages 99-119
    3. Sushmita Mitra, Sankar K. Pal
      Pages 121-143
    4. S. G. Tzafestas, G. B. Stamou, K. Watanabe
      Pages 145-161
  4. Fuzzy Controllers

    1. Front Matter
      Pages 163-163
    2. R. Jager, H. B. Verbruggen, P. M. Bruijn
      Pages 165-197
    3. Chung-Chun Kung, Sinn-Cheng Lin
      Pages 277-306
    4. Giorgio Bartolini, Antonella Ferrrara
      Pages 307-328
  5. Fuzzy Reasoning and Estimation Methodologies

    1. Front Matter
      Pages 345-345
    2. S. G. Tzafestas, S. Terzakis, A. N. Venetsanopoulos
      Pages 347-368
    3. Deba Prasad Mandal, C. A. Murthy
      Pages 387-418
  6. Applications

    1. Front Matter
      Pages 419-419
    2. M. I. Henderson, K. F. Gill
      Pages 421-449
    3. Keigo Watanabe, Sangho Jin, Spyros G. Tzafestas
      Pages 493-510
    4. Carl G. Looney
      Pages 511-527
    5. S. G. Tzafestas, F. V. Hatzivasiliou, S. K. Kaltsounis
      Pages 553-561

About this book


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.


Processing Software biomedical engineering control fuzzy logic information processing logic model network robot

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