Adaptation and Hybridization in Computational Intelligence

. Ed(s): Fister, Iztok

ISBN 10: 3319359053 / ISBN 13: 9783319359052

Editore: Springer International Publishing AG, 2016

Editor(s): Fister, Iztok. Series: Adaptation, Learning, and Optimization. Num Pages: 247 pages, 41 black & white illustrations, 1 colour illustrations, biography. BIC Classification: UYQ. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 13. Weight in Grams: 385. . 2016. Softcover reprint of the original 1st ed. 2015. Paperback. . . . . Books ship from the US and Ireland. Codice articolo V9783319359052

Riassunto:

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.

Dalla quarta di copertina:

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.

Dati bibliografici

Titolo: Adaptation and Hybridization in ...
Casa editrice: Springer International Publishing AG
Data di pubblicazione: 2016
Legatura: Brossura
Condizione: New