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Evolutionary and Swarm Intelligence Algorithms: Studies in Computational Intelligence, cartea 779

Editat de Jagdish Chand Bansal, Pramod Kumar Singh, Nikhil R. Pal
en Limba Engleză Paperback – 26 ian 2019
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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Specificații

ISBN-13: 9783030082291
ISBN-10: 3030082296
Pagini: 190
Ilustrații: X, 190 p. 57 illus., 21 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.29 kg
Ediția:Softcover reprint of the original 1st ed. 2019
Editura: Springer International Publishing
Colecția Springer
Seria Studies in Computational Intelligence

Locul publicării:Cham, Switzerland

Cuprins

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.

Textul de pe ultima copertă

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.

Caracteristici

Presents recent research in evolutionary algorithms Includes state-of-the-art research in swarm intelligence Written by experts in the field