Soft computing in systems and control technology

Bibliographic Information

Soft computing in systems and control technology

editor, S.G. Tzafestas

(World Scientific series in robotics and intelligent systems, v. 18)

World Scientific, c1999

Available at  / 8 libraries

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Note

Includes bibliographical references and index

Description and Table of Contents

Description

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.

Table of Contents

  • Neural networks in systems identification and control - supervised learning in multilayer perceptions - the back-propagation algorithm
  • identification of two-dimensional state space discrete systems using neural networks
  • neural networks for control
  • neuro-based adaptive regulator
  • local model networks and self-tuning predictive control
  • fuzzy and neuro-fuzzy systems in modelling, control and robot path planning - an on-line self constructing fuzzy modelling architecture based on neural and fuzzy concepts and techniques
  • neuro-fuzzy model-based control
  • fuzzy and neurofuzzy approaches to mobile robot path and motion planning under uncertainty
  • genetic-evolutionary algorithms - a tutorial overview of genetic algorithms and their applications
  • results from a variety of genetic algorithm applications showing the robustness of the approach
  • evolutionary algorithms in computer-aided design of integrated circuits
  • soft computing applications - soft data fusion
  • application of neural networks to computer gaming
  • coherent neural networks and their applications to control and signal processing
  • neural, fuzzy and evolutionary reinforcement learning systems - an application case study
  • neural networks in industrial and environmental applications.

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Details

  • NCID
    BA41788132
  • ISBN
    • 9810233817
  • Country Code
    si
  • Title Language Code
    eng
  • Text Language Code
    eng
  • Place of Publication
    Singapore
  • Pages/Volumes
    xxv, 479 p.
  • Size
    23 cm
  • Parent Bibliography ID
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