Details

Title Tree-Structure Based Hybrid Computational Intelligence: Theoretical Foundations and Applications (Intelligent Systems Reference Library) (Volume 2)
Author Chen, Yuehui
Binding Hardback
Edition number 2010th
Edition 2010
Pages 206
Volumes 1
Language ENG
Publisher Springer
Publication date 2010
Illustrated Yes
Features Bibliography, Illustrated, Table of Contents
Bookseller's Inventory # 4315248
ISBN 9783642047381 / 3642047386
Weight 1.08 lbs (0.49 kg)
Dimensions 9.21 x 6.14 x 0.56 in (23.39 x 15.60 x 1.42 cm)
Category Computers - General Information
Library of Congress Catalogue Number 2009936208
Dewey Decimal Code 006.3

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From the publisher

Research in computational intelligence is directed toward building thinking machines and improving our understanding of intelligence. As evident, the ultimate achievement in this field would be to mimic or exceed human cognitive capabilities including reasoning, recognition, creativity, emotions, understanding, learning and so on. In this book, the authors illustrate an hybrid computational intelligence framework and it applications for various problem solving tasks. Based on tree-structure based encoding and the specific function operators, the models can be flexibly constructed and evolved by using simple computational intelligence techniques. The main idea behind this model is the flexible neural tree, which is very adaptive, accurate and efficient. Based on the pre-defined instruction/operator sets, a flexible neural tree model can be created and evolved.

This volume comprises of 6 chapters including an introductory chapter giving the fundamental definitions and the last Chapter provides some important research challenges. Academics, scientists as well as engineers engaged in research, development and application of computational intelligence techniques and data mining will find the comprehensive coverage of this book invaluable.

From the rear cover

Research in computational intelligence is directed toward building thinking machines and improving our understanding of intelligence. As evident, the ultimate achievement in this field would be to mimic or exceed human cognitive capabilities including reasoning, recognition, creativity, emotions, understanding, learning and so on. In this book, the authors illustrate an hybrid computational intelligence framework and it applications for various problem solving tasks. Based on tree-structure based encoding and the specific function operators, the models can be flexibly constructed and evolved by using simple computational intelligence techniques. The main idea behind this model is the flexible neural tree, which is very adaptive, accurate and efficient. Based on the pre-defined instruction/operator sets, a flexible neural tree model can be created and evolved.

This volume comprises of 6 chapters including an introductory chapter giving the fundamental definitions and the last Chapter provides some important research challenges. Academics, scientists as well as engineers engaged in research, development and application of computational intelligence techniques and data mining will find the comprehensive coverage of this book invaluable.

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