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Evolutionary and swarm intelligence ...

Bansal, Jagdish Chand.

Evolutionary and swarm intelligence algorithms

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Evolutionary and swarm intelligence algorithmsedited by Jagdish Chand Bansal, Pramod Kumar Singh, Nikhil R. Pal.
其他作者:	Bansal, Jagdish Chand.
出版者:	Cham :Springer International Publishing :2019.
面頁冊數:	x, 190 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
標題:	Swarm intelligence.
電子資源:	http://dx.doi.org/10.1007/978-3-319-91341-4
ISBN:	9783319913414$q(electronic bk.)

Evolutionary and swarm intelligence algorithms
Evolutionary and swarm intelligence algorithms[electronic resource] /edited by Jagdish Chand Bansal, Pramod Kumar Singh, Nikhil R. Pal. - Cham :Springer International Publishing :2019. - x, 190 p. :ill. (some col.), digital ;24 cm. - Studies in computational intelligence,v.7791860-949X ;. - Studies in computational intelligence ;v. 216..

Swarm and Evolutionary Computation -- Particle Swarm Optimization -- Artificial Bee Colony Algorithm Variants and Its Application to Colormap Quantization -- Spider Monkey Optimization Algorithm -- Genetic Algorithm and Its Advances in Embracing Memetics -- Constrained Multi-Objective Evolutionary Algorithm -- Genetic Programming for Classification and Feature Selection -- Genetic Programming for Job Shop Scheduling -- Evolutionary Fuzzy Systems: A Case Study for Intrusion Detection Systems.

This book is a delight for academics, researchers and professionals working in evolutionary and swarm computing, computational intelligence, machine learning and engineering design, as well as search and optimization in general. It provides an introduction to the design and development of a number of popular and recent swarm and evolutionary algorithms with a focus on their applications in engineering problems in diverse domains. The topics discussed include particle swarm optimization, the artificial bee colony algorithm, Spider Monkey optimization algorithm, genetic algorithms, constrained multi-objective evolutionary algorithms, genetic programming, and evolutionary fuzzy systems. A friendly and informative treatment of the topics makes this book an ideal reference for beginners and those with experience alike.

ISBN: 9783319913414$q(electronic bk.)

Standard No.: 10.1007/978-3-319-91341-4doiSubjects--Topical Terms:

237730
Swarm intelligence.

LC Class. No.: Q337.3 / .E965 2019

Dewey Class. No.: 006.3824

Evolutionary and swarm intelligence algorithms
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245 0 0 $a Evolutionary and swarm intelligence algorithms $h [electronic resource] / $c edited by Jagdish Chand Bansal, Pramod Kumar Singh, Nikhil R. Pal.
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505 0 $a Swarm and Evolutionary Computation -- Particle Swarm Optimization -- Artificial Bee Colony Algorithm Variants and Its Application to Colormap Quantization -- Spider Monkey Optimization Algorithm -- Genetic Algorithm and Its Advances in Embracing Memetics -- Constrained Multi-Objective Evolutionary Algorithm -- Genetic Programming for Classification and Feature Selection -- Genetic Programming for Job Shop Scheduling -- Evolutionary Fuzzy Systems: A Case Study for Intrusion Detection Systems.
520 $a This book is a delight for academics, researchers and professionals working in evolutionary and swarm computing, computational intelligence, machine learning and engineering design, as well as search and optimization in general. It provides an introduction to the design and development of a number of popular and recent swarm and evolutionary algorithms with a focus on their applications in engineering problems in diverse domains. The topics discussed include particle swarm optimization, the artificial bee colony algorithm, Spider Monkey optimization algorithm, genetic algorithms, constrained multi-objective evolutionary algorithms, genetic programming, and evolutionary fuzzy systems. A friendly and informative treatment of the topics makes this book an ideal reference for beginners and those with experience alike.
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