A New Paradigm of Knowledge Engineering by Soft Computing

by Ding, Liya; Fuzzy Logic Systems Institute; International Conference on Soft Computing 1998 (Iizuka-Shi, Japan); INTERNATIONAL CONFERENCE ON SOFT COMPUTI

• ISBN13: 9789810245177
• ISBN10: 9810245173
• Format: Hardcover
• Copyright: 2001-05-01
• Publisher: WORLD SCIENTIFIC PUB CO INC

Summary

Soft computing (SC) consists of several computing paradigms, including neural networks, fuzzy set theory, approximate reasoning, and derivative-free optimization methods such as genetic algorithms. The integration of those constituent methodologies forms the core of SC. In addition, the synergy allows SC to incorporate human knowledge effectively, deal with imprecision and uncertainty, and learn to adapt to unknown or changing environments for better performance. Together with other modern technologies, SC and its applications exert unprecedented influence on intelligent systems that mimic human intelligence in thinking, learning, reasoning, and many other aspects.Knowledge engineering (KE), which deals with knowledge acquisition, representation, validation, inferencing, explanation, and maintenance, has made significant progress recently, owing to the indefatigable efforts of researchers. Undoubtedly, the hot topics of data mining and knowledge/data discovery have injected new life into the classical AI,world.This book tells readers how KE has been influenced and extended by SC and how SC will be helpful in pushing the frontier of KE further. It is intended for researchers and graduate students to use as a reference in the study of knowledge engineering and intelligent systems. The reader is expected to have a basic knowledge of fuzzy logic, neural networks, genetic algorithms, and knowledge-based systems.

Table of Contents

Series Editor's Preface	vii
Volume Editor's Preface	ix
Knowledge Engineering and Soft Computing -- An Introduction	1	(14)
Liya Ding
Part I: Fuzzy Knowledge-Based Systems
Linguistic Integrity: A Framework for Fuzzy Modeling -- AFRELI Algorithm	15	(28)
Jaito Espinosa
Joos Vandewalle
A New Approach to Acquisition of Comprehensible Fuzzy Rules	43	(16)
Hiroshi Ohno
Takeshi Furuhashi
Fuzzy Rule Generation with Fuzzy Singleton-Type Reasoning Method	59	(18)
Yan Shi
Masaharu Mizumoto
Antecedent Validity Adaptation Principle for Table Look-Up Scheme	77	(18)
Ping-Tong Chan
Ahmad B. Rad
Fuzzy Spline Interpolation in Sparse Fuzzy Rule Bases	95	(26)
Mayuka F. Kawaguchi
Masaaki Miyakoshi
Revision Principle Applied for Approximate Reasoning	121	(28)
Liya Ding
Peizhuang Wang
Masao Mukaidono
Handling Null Queries with Compound Fuzzy Attributes	149	(14)
Shyue-Liang Wang
Yu-Jane Tsai
Fuzzy System Description Language	163	(26)
Kazuhiko Otsuka
Yuichiro Mori
Masao Mukaidono
Part II: Knowledge Representation, Integration, and Discovery by Soft Computing
Knowledge Representation and Similarity Measure in Learning a Vague Legal Concept	189	(24)
MingQiang Xu
Kaoru Hirota
Hajime Yoshino
Trend Fuzzy Sets and Recurrent Fuzzy Rules for Ordered Dataset Modelling	213	(28)
Jim F. Baldwin
Trevor P. Martin
Jonathan M. Rossiter
Approaches to the Design of Classification Systems from Numerical Data and Linguistic Knowledge	241	(32)
Hisao lshibuchi
Manabu Nii
Tomoharu Nakashima
A Clustering based on Self-Organizing Map and Knowledge Discovery by Neural Network	273	(24)
Kado Nakagawa
Naotake Kamiura
Yutaka Hata
Probabilistic Rough Induction	297	(28)
Juzhen Dong
Ning Zhong
Setsuo Ohsuga
Data Mining via Linguistic Summaries of Databases: An Interactive Approach	325	(22)
Janusz Kacprzyk
Slavomir Zadrozny
About the Authors	347	(22)
Keyword Index	369