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Soft computing in systems and control technology / editor, S.G. Tzafestas

Published
Singapore ; River Edge, N.J. : World Scientific, [1999]
Copyright Date
©1999
Physical Description
1 online resource (xxv, 479 pages) : illustrations
Additional Creators
Tzafestas, S. G., 1939-
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Series
Contents
pt. I. Neural networks in system identification and control. ch. 1. Supervised learning in multilayer perceptrons: the back-propagation algorithm / S.G. Tzafestas and Y. Anthopoulos -- ch. 2. Identification of two-dimensional state space discrete systems using neural networks / D. Wang and A. Zilouchian -- ch. 3. Neural networks for control / R.J. Mitchell -- ch. 4. Neuro-based adaptive regulator / T. Tsuji, B.H. Xu and M. Kaneko -- ch. 5. Local model networks and self-tuning predictive control / P.J. Gawthrop and E. Ronco -- pt. II. Fuzzy and neuro-fuzzy systems in modelling, Control and robot path planning. ch. 6. An on-line self constructing fuzzy modeling architecture based on neural and fuzzy concepts and techniques / S.G. Tzafestas and K.C. Zikidis -- ch. 7. Neuro-fuzzy model based control / D. Matko, K. Kavsek-Biasizzo and J. Kocijan -- ch. 8. Fuzzy and neurofuzzy approaches to mobile robot path and motion planning under uncertainty / C.S. Tzafestas and S.G. Tzafestas -- pt. III. Genetic-evolutionary algorithms -- ch. 9. A tutorial overview of genetic algorithms and their applications / S.G. Tzafestas, M.-P. Saltouros and M. Markaki -- ch. 10. Results from a variety of genetic algorithm applications showing the robustness of the approach / W.D. Potter, S.M. Bhandarkar and D.J. D'Angelo -- ch. 11. Evolutionary algorithms in computer-aided design of integrated circuits / R. Drechsler, N. Drechsler, B. Becker and H. Esbensen -- pt. IV. Soft computing applications. ch. 12. Soft data fusion / C.G. Looney and Y. Varol -- ch. 13. Application of neural networks to computer gaming / N. Baba -- ch. 14. Coherent neural networks and their applications to control and signal processing / A. Hirose -- ch. 15. Neural, fuzzy and evolutionary reinforcement learning systems: an application case study / D.A. Linkens and H.O. Nyongesa -- ch. 16. Neural networks in industrial and environmental applications / G.C. Smith and C.L. Wrobel.
Summary
Soft computing is a branch of computing which, unlike hard computing, can deal with uncertain, imprecise and inexact data. The three constituents of soft computing are fuzzy-logic-based computing, neurocomputing, and genetic algorithms. Fuzzy logic contributes the capability of approximate reasoning, neurocomputing offers function approximation and learning capabilities, and genetic algorithms provide a methodology for systematic random search and optimization. These three capabilities are combined in a complementary and synergetic fashion. This book presents a cohesive set of contributions dealing with important issues and applications of soft computing in systems and control technology. The contributions include state-of-the-art material, mathematical developments, fresh results, and how-to-do issues. Among the problems studied via neural, fuzzy, neurofuzzy and genetic methodologies are: data fusion, reinforcement learning, approximation properties, multichannel imaging, signal processing, system optimization, gaming, and several forms of control. The book can serve as a reference for researchers and practitioners in the field. Readers can find in it a large amount of useful and timely information, and thus save considerable effort in searching for other scattered literature.
Subject(s)
ISBN
9789812816528 (electronic bk.)
9812816526 (electronic bk.)
9810233817
9789810233815
Bibliography Note
Includes bibliographical references and index.
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