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Adaptation and Hybridization in Computational Intelligence

This carefully edited book takes a walk through recent advances in adaptation and hybridization in the Computational Intelligence (CI) domain. It consists of ten chapters that are divided into three parts. The first part illustrates background information and provides some theoretical foundation tackling the CI domain, the second part deals with the adaptation in CI algorithms, while the third part focuses on the hybridization in CI.

This book can serve as an ideal reference for researchers and students of computer science, electrical and civil engineering, economy, and natural sciences that are confronted with solving the optimization, modeling and simulation problems. It covers the recent advances in CI that encompass Nature-inspired algorithms, like Artificial Neural networks, Evolutionary Algorithms and Swarm Intelligence –based algorithms.

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Detail Information
Series Title
Adaptation, Learning, and Optimization
Call Number
006.3 ADA a
Publisher
Cham, Switzerland : Springer.,
Collation
X, 237
Language
English
ISBN/ISSN
978-3-319-14400-9
Classification
006.3
Content Type
text
Media Type
computer
Carrier Type
online resource
Edition
Ed. 1
Subject(s)
Artificial Intelligence
Computational Intelligence
Specific Detail Info
-
Statement of Responsibility
Other Information
Cataloger
umi
Source
https://link.springer.com/content/pdf/10.1007/978-3-319-14400-9.pdf?pdf=button
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