New Paradigm Of Knowledge Engineering By Soft Computing, A
Will be published approx. on 12. March 2001
Book
Hardback
388 pages
978-981-02-4517-7 (ISBN)
Description
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.
More details
Series
Language
English
Place of publication
Singapore
Singapore
Target group
College/higher education
Professional and scholarly
Product notice
sewn/stitched
Cloth over boards
Dimensions
Height: 223 mm
Width: 156 mm
Thickness: 41 mm
Weight
685 gr
ISBN-13
978-981-02-4517-7 (9789810245177)
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Schweitzer Classification
Person
Content
Knowledge engineering and soft computing - an introduction, L.-Y. Ding. Part 1 Fuzzy knowledge-based systems: linguistic integrity - a framework for fuzzy modelling, AFRELI algorithm, J. Espinosa and J. Vandewalle; a new approach to acquisition of comprehensible fuzzy rules, H. Ohno and T. Furuhashi; fuzzy rule generation with fuzzy singleton-type reasoning method, Y. Shi and M. Mizumoto; antecedent validity adaptation principle for table look-up scheme, P.-T. Chan and A.B. Rad; fuzzy spline interpolation in sparse fuzzy rule bases, M.F. Kawaguchi and M. Miyakoshi; revision principles applied for approximate reasoning, L.-Y. Ding et al; handling null queries with compound fuzzy attributes, S.-L. Wang and Y.-J. Tsai; fuzzy system description language, K. Otsuka et al. Part 2 Knowledge representation, integration and discovery by soft computing: knowledge representation and similarity measures in learning a vague legal concept, M.Q. Xu et al; trend fuzzy sets and recurrent fuzzy rules for ordered dataset modelling, J.F. Baldwin et al; approaches to the design of classification systems from numerical data and linguistic knowledge, H. Ishibuchi et al; a clustering based on self-organizing map and knowledge discovery by neural network, K. Nakagawa et al; probabilistic rough induction, J.-Z. Dong et al; data mining via linguistic summaries of databases - an interactive approach, J. Kacprzyk and S. Zadrozny. (Part contents).