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Recent Advances in Swarm Intelligence and Evolutionary Computation

Author: Xin-She Yang
Publisher: Cham : Springer, 2015.
Series: Studies in Computational Intelligence ; 585; SpringerLink : Bücher
Edition/Format:   eBook : EnglishView all editions and formats
Summary:
This timely review volume summarizes the state-of-the-art developments in nature-inspired algorithms and applications with the emphasis on swarm intelligence and bio-inspired computation. Topics include the analysis and overview of swarm intelligence and evolutionary computation, hybrid metaheuristic algorithms, bat algorithm, discrete cuckoo search, firefly algorithm, particle swarm optimization, and harmony search  Read more...
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Details

Material Type: Internet resource
Document Type: Internet Resource
All Authors / Contributors: Xin-She Yang
ISBN: 9783319138268 331913826X
OCLC Number: 903305642
Description: Online-Ressource (XI, 300 p. 94 illus., 15 illus. in color, online resource)
Series Title: Studies in Computational Intelligence ; 585; SpringerLink : Bücher
Responsibility: edited by Xin-She Yang.

Abstract:

This timely review volume summarizes the state-of-the-art developments in nature-inspired algorithms and applications with the emphasis on swarm intelligence and bio-inspired computation. Topics include the analysis and overview of swarm intelligence and evolutionary computation, hybrid metaheuristic algorithms, bat algorithm, discrete cuckoo search, firefly algorithm, particle swarm optimization, and harmony search as well as convergent hybridization. Application case studies have focused on the dehydration of fruits and vegetables by the firefly algorithm and goal programming, feature selection by the binary flower pollination algorithm, job shop scheduling, single row facility layout optimization, training of feed-forward neural networks, damage and stiffness identification, synthesis of cross-ambiguity functions by the bat algorithm, web document clustering, truss analysis, water distribution networks, sustainable building designs and others. As a timely review, this book can serve as an ideal reference for graduates, lecturers, engineers and researchers in computer science, evolutionary computing, artificial intelligence, machine learning, computational intelligence, data mining, engineering optimization and designs.

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