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CRC Press Inc
22 June 2000
Algorithms & data structures; Machine learning
Evolutionary computing uses genetic algorithms to solve problems through a learning process. Each cycle of the application builds on information learned in its previous run, therefore its problem-solving evolves . In this book, the authors describe the basic principles of evolutionary computing, genetic algorithms, programming, and applications. Detailed coverage of binary and real encoding, including selection, crossover, and mutation, is included in two chapters. Discussion of evolution strategies covers strategy principles, mutations, recombination, and optimization. Applications for evolutionary computing are varied. Some of those covered in this book include: decision support, training & design of neural networks, pattern recognition, genetic programming, and cellular automata.
By:   D. Dumitrescu, A. Dumitrescu, C Jain Lakhmi, Beatrice Lazzerini
Imprint:   CRC Press Inc
Country of Publication:   United States
Volume:   18
Dimensions:   Height: 235mm,  Width: 156mm,  Spine: 28mm
Weight:   744g
ISBN:   9780849305887
ISBN 10:   0849305888
Series:   International Series on Computational Intelligence
Pages:   424
Publication Date:   22 June 2000
Audience:   College/higher education ,  Professional and scholarly ,  Further / Higher Education ,  Undergraduate
Format:   Hardback
Publisher's Status:   Active

Reviews for Evolutionary Computation

offers a presentation of the main ideas, models, and algorithms of evolutionary computation. Anyone who is inspired by the work of L. Davis or D.E. Goldberg to use evolutionary computation as a tool in hos/her daily work will find a complete overview of techniques and strategiesAnyone interested in optimization or search problems can find useful ideas, methods, and algorithms. - Journal of Chemometrics, 2002


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