Fuzzy Theory Systems, Four-Volume Set book cover

Fuzzy Theory Systems, Four-Volume Set

Techniques and Applications

Applications of fuzzy theory (often referred to as "fuzzy logic") are maturing and multiplying at a phenomenal rate, and a comprehensive treatment of these real-world techniques and applications is now very timely. Unlike traditional computer logic involving clear true or false decisions, a fuzzy logic system chooses what is most true after "considering" several contributing and possibly conflicting variables. Examples of practical devices using fuzzy computer decision-making are thermostats that respond to a combination of temperature and humidity (comfort factors), an elevator that considers how crowded a car is rather than just its proximity to the desired floor, and a camera that integrates the variables affecting picture quality. These volumes will present a logical progression from implementation and modeling techniques to industrial/commercial applications to fuzzy neural and adaptive fuzzy systems.

Audience
Students, research workers, and practitioners in engineering and computer science.

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Published: September 1999

Imprint: Academic Press

ISBN: 978-0-12-443870-5

Reviews

  • level of these texts makes them suitable for use on senior graduate level courses and the contributors are some of the leading researchers on the subject. . . .this four volume set is very desirable for anyone involved with fuzzy modeling control and signal processing."
    --MIKE J. GRIMBLE, University of Strathclyde, Glasgow, U.K.


    "This valuable compendium . . . most definitely belongs in the libraries of all institutions where teaching or research on fuzzy logic and its applications is conducted."
    --CHOICE, June 2000
    "As the foreword notes, this valuable compendium of an extensive array of applications of fuzzy set theory emphasizes the practical applications of fuzzy logic, using fuzzy if-then rules. It most definitely belongs in the libraries of all institutions where teaching or research on fuzzy logic and its applications is conducted at any level."
    --CHOICE, July/August 2000

Contents

  • Contents of Volume 1: A. DeGloria, P. Ferrari, D. Grosso, M. Olivieri, and I. Puglisi, Implementation Techniques and Their Applications. H. Ishibuchi and M. Nii, Neural Networks for Fuzzy Rule Approximation. J.V. de Oliviera and J.M. Lemos, Fuzzy System Interface Optimizers in Various Systems Problems. S.H. Nasution, Fuzzy Theory to Critical Path Methods. J. Virant, N. Zimic, and M. Mraz, Fuzzy Sequential Circuits and Automata. K. Hirota and W. Pedrycz, Or/And Neurons in Fuzzy Systems. M. Russo, Hybrid Fuzzy Learning Theory in Systems Modeling. A.J.B. Diz, Fuzzy Systems Based on Petri Net Formalism. W. Pedrycz and J.V. de Oliviera, Optimization Techniques in the Design of Fuzzy Models. W. Pedrycz, Modeling Relationships in Data: From Contingency Tables to Fuzzy Multimodels. Y.-C. Hsu and G. Chen, Fuzzy Dynamical Modeling Techniques for Nonlinear Control Systems and Their Application to Multiple-Input Multiple-Output (MIMO) Systems. E. Deeba, A. de Korvin, and S. Xie, Fuzzy Set Theory to Difference and Functional Equations and Their Utilization in Modeling Diverse Systems. Y. Jin and J. Jiang, Neural Network Based Fuzzy System Identification and Their Application in the Control of Complex Systems. C.-M. Liaw and Y.-S. Kung, Fuzzy Control with Reference Model Following Response. W. Pedrycz, Fuzzy Set Based Models of Neurons and Knowledge-Based Network. L. Wang, R. Langari, and J. Yen, Identifying Fuzzy Rule Based Models Using Orthogonal Transformation and Backpropagation. C.-T. Sun and H.-J. Chiu, Evolutionary Neuro-Fuzzy Modeling. Subject Index.Contents of Volume 2: A. Aoyama, F.J. Doyle III, and V. Venkatasubramanian, Fuzzy Neural Network Systems for Nonlinear Chemical Process Control Systems. J.L. Koning, Fuzzy Theory in Material Selection for Mechanical Design Problems. G.D. Mandyam and M.D. Srinath, Applications of Fuzzy System Theory to Telecommunications. N. Sepehri, T. Corbet, and P.D. Lawrence, Hydraulically Actuated Industrial Robots. H.A. Malki and G. Chen, Design and Stability Analysis of Fuzzy Proportional-Integral-Derivative (PID) Control Systems and Their Industrial Applications. P. Bose, L. Lietard, and O. Pivert, Database Management Systems. S.-M. Chen, Document Retrieval Systems. M. Berenguel, F.R. Rubio, E.P. Camacho, and F. Gordillo, Fuzzy Logic Control of Solar Power Plants. H.J. Caulfield, J. Ludman, and J. Shamir, Fuzzy Metrology. C.V. Jawahar and A.K. Ray, Fuzzy Statistics in Digital Image Analysis. Y. Zhang, Digital Image Transformation. K.-S. Cheng, J.-S. Lin, and C.-W. Mao, Comparative Analysis of Neural Network Systems and Fuzzy Systems in Medical Image Segmentation. A.-Y. Chen, K.-A. Wen, and F.-S. Leou, Image Processing Based on the Human Visual System Model. I.H. Suh and T.W. Kim, Fuzzy Logic-Based Visual Feedback Control. S. Abe, Fuzzy Rules Determination and Their Application to Pattern Classification. H. Ishibuchi, T. Nakashima, and T. Murata, Genetic Algorithm Based Methods for Designing Compact Fuzzy Classification Systems. T.D. Pham and H. Yan, Combination of Handwritten-Numeral Classifiers with Fuzzy Integral. Subject Index.Contents of Volume 3: Y.-H. Kuo and J.-P. Hsu, Fuzzy Neural Network Systems. K.M. Lee and H. Lee-Kwang, Fuzzy Inference Neural Networks for Fuzzy Model Improvement. C.-F. Juang, H.-W. Nein, and C.-T. Lin, Integrated Neural Network Based Fuzzy Logic Control Systems. S.I. Chang, Neural Fuzzy System Techniques and Applications for Production Quality Control. K. Kiguchi and T. Fukuda, Fuzzy-Neural Network Techniques in Robotic Object Manipulation. A. Konar and S. Pal, Modeling Cognition with Fuzzy Neural Nets. C.-T. Lin, I.F. Chung, and Y.C. Lu, Neural Fuzzy Systems for Processing Numerical and Linguistic Information. K.C. Chan, Intelligent PID Controllers. B.-S. Chen and Y.-M. Cheng, Fuzzy Theory Via Control Techniques for Tracking Algorithms for Uncertain Nonlinear Systems. Y.R. Hwang, Fuzzy Smoothing Algorithms for Control Systems. P. Lee, G.J. Jeon, and K.K. Lee, Fuzzy Theory in the Validity of Complexity Reduction by Means of Decomposition of Multivariable Fuzzy Systems. F. Klawonn and R. Kruse, Control Systems Based on Knowledge-Based Interpolation. B.M. Novakovic, Adaptive Fuzzy Logic Control Synthesis Without Any Fuzzy Rule Base. C.-Y. Su and Y. Stepanenko, Fuzzy Adaptive Control Techniques for Nonlinear Systems and Their Application. Y.-M. Park, U.-C. Moon, and K.Y. Lee, On-Line Self-Organizing Fuzzy Logic Controller Using Fuzzy Auto-Regressive Moving Average (FARMA) Model. T. Jiang and Y. Li, Fuzzy Theory in Generalized Defuzzification Methods and Their Utilization in Parameter Learning Techniques. R. Palm, Optimal Adjustment of Scaling for Fuzzy Controllers Using Correlation Techniques. H. Narazaki and A.L. Ralescu, Translation and Extraction Problems for Neural and Fuzzy Systems: Bridging Over Distributed Knowledge Representation in Multi-Layered Neural Networks and Local Knowledge Representations in Fuzzy Systems. J. Anbe and T. Tobi, Fuzzy Set System Applications to Medical Diagnosis. Subject Index.

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