new book

W. Pedrycz (
Mon, 1 Jul 1996 11:59:53 +0200

Dear BISC Members:

please find enclosed an info about a new book on fuzzy modelling

Best regards

Fuzzy Sets and Fuzzy Logic
Systems and Control Theory
Control Systems

Fuzzy Modelling

Paradigms and Practice

edited by
Witold Pedrycz
University of Manitoba, Winnipeg, Canada


Fuzzy Modelling: Paradigms and Practice provides an
up-to-date and authoritative compendium of fuzzy models,
identification algorithms and applications. Chapters in this book have
been written by the leading scholars and researchers in their
respective subject areas. Several of these chapters include both
theoretical material and applications. The editor of this volume has
organized and edited the chapters into a coherent and uniform
The objective of this book is to provide researchers and practitioners
involved in the development of models for complex systems with an
understanding of fuzzy modelling, and an appreciation of what makes
these models unique. The chapters are organized into three major parts
covering relational models, fuzzy neural networks and rule-based
models. The material on relational models includes theory along with a
large number of implemented case studies, including some on speech
recognition, prediction, and ecological systems. The part on fuzzy
neural networks covers some fundamentals, such as neurocomputing,
fuzzy neurocomputing, etc., identifies the nature of the relationship
that exists between fuzzy systems and neural networks, and includes
extensive coverage of their architectures. The last part addresses the
main design principles governing the development of rule-based models.

Fuzzy Modelling: Paradigms and Practice provides a wealth of
specific fuzzy modelling paradigms, algorithms and tools used in
systems modelling. Also included is a panoply of case studies from
various computer, engineering and science disciplines. This should be
a primary reference work for researchers and practitioners developing
models of complex systems.

Contents and Contributors:
Part 1: Modelling with Fuzzy Sets. 1.1. Fuzzy
Models: Methodology, Design, Applications, and Challenges; W.
Pedrycz. Part 2: Relational Models. 2.1.
Fundamentals of Fuzzy Relational Calculus; S. Gottwald.
2.2. Max-Min Relational Networks; A. Blanco, et al.
2.3. Relational Calculus in Designing Fuzzy Petri Networks;
H. Scarpelli, F. Gomide. 2.4. Prediction in Relational
Models; J. Valente de Oliveira. 2.5. Implementing a Fuzzy
Relational Network for Phonetic Automatic Speech Recognition; C.A.
Reyes-Garcia, W. Bandler. 2.6. Fuzzy Ecological Models; S.
Marsili Libelli, P. Cianchi. Part 3: Fuzzy Neural Networks.
3.1. Fuzzy Neural Networks: Capabilities; J. Buckley, E.
Eslani. 3.2. Development of Fuzzy Neural Networks; H.
Ishibuchi. 3.3. Designing Fuzzy Neural Networks Through
Backpropagation; D. Nauck, R. Kruse. Part 4: Rule-Based
Modelling. 4.1. Foundations of Rule-based Computations in
Fuzzy Models; A. Kandel, et al. 4.2. Evolutionary Learning
of Rules: Competition and Cooperation; A. Bonarini. 4.3.
Logical Optimization of Rule-based Models; R. Rovatti.
4.4. Interpretation and Completion of Fuzzy Rules; T.
Sudkamp, R.J. Hammel II. 4.5 Hyperellipsoidal
Clustering; Y. Nakamori, M. Ryoke. 4.6. Fuzzy Rule-based
Models in Computer Vision; J.M. Keller, et al. 4.7.
Forecasting in Rule-based Systems; A. Zardecki. Subject Index.

Kluwer Academic Publishers, Boston

Date of publishing: March 1996
416 pp.
ISBN: 0-7923-9703-7
NLG: 230.00
USD: 125.00
GBP: 88.75


Author: Witold Pedrycz
Title: Fuzzy Modelling
( ) Hardbound / ISBN: 0-7923-9703-7
NLG: 230.00 USD: 125.00 GBP: 88.75


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<HDR>:Pedrycz, Witold; Fuzzy Modelling
<BT>Fuzzy Modelling
<ST>Paradigms and Practice
<AUT>Witold Pedrycz
<KW>Fuzzy Sets and Fuzzy Logic
Systems and Control Theory
Control Systems
<PD>March 1996