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Series F: Computer and Systems Sciences, Vol. 162
Springer-Verlag Berlin Heidelberg GmbH
Computational Intelligence:
Soft Computing
and Fuzzy-Neuro Integration
with Applications
Edited by
Okyay Kaynak
Faculty of Engineering
Bogazi!j:i University
TR-80815 Istanbul, Turkey
Lotfi A. Zadeh
Computer Science Division
U niversity of California at Berkeley
Berkeley, CA 94720-1776, USA
Burhan
Tiirkşen
University of Toronto
Ontario M5S 3G8, Canada
Imre J. Rudas
Bânki Donat Polytechnic
N epszinMz u. 8
H-I081 Budapest, Hungary
Springer
Published in cooperation with NATO Scientific Affairs Division
Proceedings of the NATO Advanced Study Institute
on Soft Computing and Its Applications
held at Manavgat, Antalya, Turkey, August 21-31,1996
Llbrary of Congress Cataloglng-In-Publication Data
Computational intell igence : soft'computing and fuzzy-neuro
integratlon with applications / edited by Okyay Kaynak ... [et al. 1.
p. cm. -- (NATD ASI series. Serles F. Computer and systems
sciences ; voI. 162)
"Proceedings of the NATD Advanced Study Institute on Computational
Intelligence (Fuzzy-Neural Integration) held at Antalya, Turkey.
Augustt 21-31. 1996"--CIP verse t.p.
Includes bibliographical references and index.
ISBN 978-3-642-63796-4 ISBN 978-3-642-58930-0 (eBook)
DOI 10.1007/978-3-642-58930-0
1. Soft computing--Congresses. 2. Neural networks (Computer
science)--Congresses. 3. Fuzzy systems--Congresses. 1. Kaynak.
Dkyay, 1948- II. NATD Advanced Study Institute on Computational
Intelligence (Fuzzy-Neural Integration) (1996: Antalya. Turkey)
III. Ser ies: NATD ASI series. Ser ies F. Computer and systems
sciences ; no. 162.
QA76.9.S63C66 1998
006.3--dc21 98-25071
CIP
ACM Subject Classification (1998): 1.2, J.2, 1.5, F.I,C.I, J.6
ISBN 978-3-642-63796-4
This work is subject to copyright. AH rights are reserved, whether the whole or part of the
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use must always be obtained from Springer-Verlag. Violations are liable for prosecution under
the German Copyright Law.
© Springer-Verlag Berlin Heidelberg 1998
Originally published by Springer-Verlag Berlin Heidelberg New York in 1998
Softcover reprint of the hardcover 1s t edition 1998
Typesetting: Camera-ready by authors/editors
Printed on acid-free paper
SPIN: 10552716 45/3142 - 5 4 3210
Preface
This book is a collection of some of the papers that were presented during a
NATO Advanced Study Institute (ASI) on Soft Computing and Its Applications
that was held in Manavgat, Antalya, Turkey, on 21-31 August 1996. The ASI had
the goal of creating an opportunity for the engineers and the scientists working in
the emerging field of soft computing (SC) to come together in an informal
atmosphere and to discuss and disseminate knowledge on the application aspects
of soft computing techniques, especially in intelligent control systems and
mechatronics. Two particular areas that the institute put a special emphasis on are
(1) how to achieve a synergistic combination of the main constituents of soft
computing and (2) how can such a combination be applied to achieve a high
machine intelligence quotient (MIQ).
In the opening stages of the institute, it was stated that soft computing is a
consortium of computing methodologies which provide a foundation for the
conception, design, and deployment of intelligent systems and aims at the
formalization of the remarkable human ability to make rational decisions in an
environment of uncertainty and imprecision. It was pointed out that soft computing
provides a better and more natural foundation for intelligent systems.
The institute asserted that traditional "hard computing" (HC), based on binary
logic, crisp systems, numerical analysis, and crisp software, has the characteristics
of precision and categoricity, while soft computing has those of approximation and
dispositionality. Although in the former, imprecision and uncertainty are
undesirable properties, in the latter the tolerance for imprecision and uncertainty is
exploited to achieve tractability, lower cost, high MIQ, and economy of
communication.
The papers presented during the institute considered the principal constituents of
soft computing, namely fuzzy logic (FL), neurocomputing (NC), genetic
computing (GC), and probabilistic reasoning (PR), the relation between them and
their fusion in industrial applications. In this perspective, it was discussed that the
principal contribution of fuzzy logic relates to its provision of a foundation for
approximate reasoning, while neural network theory provides an effective
methodology for learning from examples, and probabilistic reasoning systems
furnish computationally effective techniques for representing and propagating
probabilities and beliefs in complex inference networks. Several presentations
described a number of practical applications ranging from helicopter control, fault
diagnosis, and smart appliances to speech and pattern recognition and planning
under uncertainty.
VI
Novel concepts such as computing with words and information granulation were
also discussed during the AS!. Prof. Zadeh argued that information granularity lies
at the center of human reasoning and concept formation, and plays a pivotal role in
fuzzy logic and computing with words.
A number of presentations concentrated on the connections between neural
networks and fuzzy logic. Use of vectoral neural networks in soft computing and
modelling fuzzy reasoning by neural networks were among the topics of
discussion. On the fuzzy logic side, fuzzy data analysis and fuzzy decision support
systems were discussed in depth.
Some speakers concentrated on the software and hardware architectures for soft
computing. Computer vision was a major topic of discussion as an application
area. Robotics and mechatronics applications were also discussed. It was agreed
that the successful applications of soft computing and the resulting rapid growth of
interest in this emerging field indicate to us that, using Zadeh's words, "soft
computing is likely to play an important role in science and engineering, but
eventually its influence may extend much farther. In many ways, soft computing
represents a significant paradigm shift in the aims of computing-a shift which
reflects the fact that the human mind, unlike present day computers, possesses a
remarkable ability to store and process information which is pervasively imprecise,
uncertain and lacking in categoricity".
Some of the papers of the book are not exactly the same as they were presented
during the AS!. The authors had ample time to modify the contents of their
contributions and to put them into a more appropriate form for a book.
Additionally, the book also contains two papers by Prof. Dubois, who could not
participate in the ASI as was originally planned.
The title of the book is slightly different from the title of the institute, and the
book itself is divided into six main parts, namely (i) computational intelligence, (ii)
foundations of fuzzy theory, (iii) fuzzy systems, (iv) neural networks, (v) data
analysis, and (vi) applications. Each part has a number of papers authored by
leading experts of the field. The first part starts with a paper by Prof. Zadeh
himself in which he expresses his views on the roles of soft computing and fuzzy
logic in the conception, design, and deployment of information/intelligent systems.
Finally, on behalf of all the editors of the book, I would like to thank NATO
Scientific Affairs Division for their support of the AS!. I hope that the readers will
find the resulting volume interesting and beneficial. Additionally, I would like to
acknowledge the facilities provided by the National University of Singapore
during the final editing stages of this book.
March 1998 Okyay Kaynak
Contents
Preface .................................................................................................................. v
Part 1 Computational Intelligence
Roles of Soft Computing and Fuzzy Logic in the Conception, Design
and Deployment of InformationlIntelligent Systems ............................................... 1
L. A. Zadeh
Computational Intelligence Defined - By Everyone! ........................................... 10
1. C. Bezdek
Computational Intelligence: Extended Truth Tables and Fuzzy Normal
Forms .................................................................................................................... 38
I. B. Tiirkgen
Uncertainty Theories by Modal Logic .................................................................. 60
G. Resconi
Part 2 Foundations of Fuzzy Theory
Sup-T Equations: State of the Art ......................................................................... 80
B. De Baets
Measures of Specificity ......................................................................................... 94
R. R. Yager
What's in a Fuzzy Membership Value? ............................................................... 114
S. Kundu
New Types of Generalized Operations ............................................................... 128
l. 1. Rudas, O. Kaynak
VIII
Part 3 Fuzzy Systems
Intelligent Fuzzy System Modeling ..................................................................... 157
1. B. Tiirk kn
Fuzzy Inference Systems: A Critical Review ...................................................... 177
V Cherkassky
Fuzzy Decision Support Systems ........................................................................ 198
H-J. Zimmermann
Neuro-Fuzzy Systems .......................................................................................... 230
R. Kruse, D. Nauck
Fuzzified Petri-Nets and Their Application to Organising Supervisory
Controller ............................................................................................................ 260
G. M Dimirovski
Part 4 Neural Networks,
A Review of Neural Networks with Direct Learning Based on Linear
or Non-linear Threshold Logics ......................................................................... 283
D. M Dubois
The Morphogenetic Neuron ................................................................................ 304
G. Resconi
Boolean Soft Computing by Non-linear Neural Networks with
Hyperincursive Stack Memory ............................................................................ 333
D. M Dubois
Part 5 Data Analysis
Using Competitive Learning Models for Multiple Prototype Classifier
Design ................................................................................................................. 352
J. C. Bezdek, S. G. Lim, and T. Reichherzer
Fuzzy Data Analysis ............................................................................................ 381
H-J. Zimmermann
Probabilistic and Possibilistic Networks and How To Learn Them
from Data ............................................................................................................ 403
C. Borgelt, R. Kruse
IX
Part 6 Applications
Image Pattern Recognition Based on Fuzzy Technology .................................... 427
K. Hirota, Y Arai, Y Nakagawa
Fuzzy Sets and the Management of Uncertainty in Computer Vision ................. 434
J M Keller
Intelligent Robotic Systems Based on Soft Computing
- Adaptation, Learning and Evolution ................................................................. 450
T. Fukuda, K. Shimojima
Hardware and Software Architectures for Soft Computing ................................. 482
R. Paluzzi
Fuzzy Logic Control for Design and Control of Manufacturing
Systems ................................................................................................................ 496
B. Tan
Applications of Intelligent Multiobjective Fuzzy Decision Making .................... 514
E. H Ruspini
A Product Life Cycle Information Management System Infrastructure
with CAD/CAE/CAM, Task Automation, and Intelligent Support
Capabilities .......................................................................................................... 521
H P. Frisch
Roles of Soft Computing and Fuzzy Logic
in the Conception, Design and Deployment
of Information/Intelligent Systems!
Lotfi A. Zadeh
University of California at Berkeley, Berkeley, CA 94720-1776, USA
Abstract. The essence of soft computing is that, unlike the traditional, hard
computing, it is aimed at an accommodation with the pervasive imprecision of the
real world. Thus, the guiding principle of soft computing is: ' ... exploit the
tolerance for imprecision, uncertainty and partial truth to achieve tractability,
robustness, low solution cost and better rapport with reality.' In the final analysis,
the role model for soft computing is the human mind.
Soft computing is not a single methodology. Rather, it is a partnership. The
principal partners at this juncture are fuzzy logic, neurocomputing, genetic
computing and probabilistic computing, with the latter subsuming chaotic systems,
belief networks and parts of learning theory.
In coming years, the ubiquity of intelligent systems is certain to have a profound
impact on the ways in which man-made intelligent systems are conceived,
designed, manufactured, employed and interacted with. It is in this perspective that
the basic issues relating to soft computing and intelligent systems are addressed in
this paper.
1. Introduction
To see the evolution of fuzzy logic in a proper perspective, it is important to note
that we are in the throes of what is popularly called the information revolution.
The artifacts of this revolution are visible to all. The Internet, World Wide Web,
cellular phones, facsimile machines and portable computers with powerful
information processing capabilities have all become a part of everyday reality. The
centrality of information in almost everything that we do is a fact that few would
care to challenge.
Much less visible, but potentially of equal or even greater importance, is what
might be called the intelligent systems revolution. The artifacts of this revolution
are man-made systems which exhibit an ability to reason, learn from experience
and make rational decisions without human intervention. I coined the term MIQ
(machine intelligence quotient) to describe a measure of intelligence of man-made
I A slightly different version of this paper has previously been published under a slightly
different title in BT Technology Journal, 14, No 4, pp 32-36 (October 1996).
O. Kaynak et al. (eds.), Computational Intelligence: Soft Computing and Fuzzy-Neuro
Integration with Applications
© Springer-Verlag Berlin Heidelberg 1998
