Advances in Computational Intelligence: Theory and Practice / Edition 1

Advances in Computational Intelligence: Theory and Practice / Edition 1

ISBN-10:
3642077587
ISBN-13:
9783642077586
Pub. Date:
12/10/2010
Publisher:
Springer Berlin Heidelberg
ISBN-10:
3642077587
ISBN-13:
9783642077586
Pub. Date:
12/10/2010
Publisher:
Springer Berlin Heidelberg
Advances in Computational Intelligence: Theory and Practice / Edition 1

Advances in Computational Intelligence: Theory and Practice / Edition 1

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Overview

The 30 coherently written chapters by leading researchers presented in this anthology are devoted to basic results achieved in computational intelligence since 1997. The book provides complete coverage of the core issues in the field, especially in fuzzy logic and control as well as for evolutionary optimization algorithms including genetic programming, in a comprehensive and systematic way. Theoretical and methodological investigations are complemented by prototypic applications for design and management tasks in electrical engineering, mechanical engineering, and chemical engineering.

This book will become a valuable source of reference for researchers active in computational intelligence. Advanced students and professionals interested in learning about and applying advanced techniques of computational intelligence will appreciate the book as a useful guide enhanced by numerous examples and applications in a variety of fields.


Product Details

ISBN-13: 9783642077586
Publisher: Springer Berlin Heidelberg
Publication date: 12/10/2010
Series: Natural Computing Series
Edition description: Softcover reprint of hardcover 1st ed. 2003
Pages: 326
Product dimensions: 6.10(w) x 9.25(h) x 0.24(d)

Table of Contents

1 Introduction.- I. Fuzzy Logic.- 2 Mathematical Foundations of Fuzzy Inference.- 3 Data-Based Fuzzy Modeling for Complex Applications.- 4 Fuzzy Modeling to Cope with Ambiguities.- II. Evolutionary Algorithms.- 5 Theory of Evolutionary Algorithms and Genetic Programming.- 6 Design of Evolutionary Algorithms and Applications in Surface Reconstruction.- 7 Genetic Programming and Its Application in Machining Technology.- III. Machine Learning and Optimization.- 8 Novel Learning Tasks, Optimization, and Their Application.
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