Advances in Computational Intelligence
Theory and Practice
Published on 27. November 2002
Book
Hardback
X, 326 pages
978-3-540-43269-2 (ISBN)
Description
In this book, comprising recent research of leading researchers, a broad variety of problems is introduced, motivated, and then new results on these problems are presented. This handbook-like volume is for readers with theoretical as well as practical background knowledge about Computational Intelligence.
Reviews / Votes
From the reviews:
"The 30 coherently written chapters by leading researchers presented in this anthology are devoted to basic results achieved in computational intelligence since 1997. . 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." (PHINEWS, Vol. 2, October 2002)
More details
Series
Edition
2003 ed.
Language
English
Place of publication
Berlin
Germany
Publishing group
Springer Berlin
Target group
Professional and scholarly
Professional/practitioner
Illustrations
X, 326 p.
Dimensions
Height: 241 mm
Width: 160 mm
Thickness: 23 mm
Weight
670 gr
ISBN-13
978-3-540-43269-2 (9783540432692)
DOI
10.1007/978-3-662-05609-7
Schweitzer Classification
Other editions
Additional editions
Hans-Paul Schwefel | Ingo Wegener | K.D. Weinert
Advances in Computational Intelligence
Theory and Practice
Book
12/2010
Springer
€106.99
Shipment within 7-9 days
Content
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.