Nature-inspired Computation in Engineering: 637 - Rilegato

 
9783319302331: Nature-inspired Computation in Engineering: 637

Sinossi

This timely review book summarizes thestate-of-the-art developments in nature-inspired optimization algorithms andtheir applications in engineering. Algorithms and topics include the overviewand history of nature-inspired algorithms, discrete firefly algorithm, discretecuckoo search, plant propagation algorithm, parameter-free bat algorithm,gravitational search, biogeography-based algorithm, differential evolution,particle swarm optimization and others. Applications include vehicle routing,swarming robots, discrete and combinatorial optimization, clustering ofwireless sensor networks, cell formation, economic load dispatch, metamodeling,surrogated-assisted cooperative co-evolution, data fitting and reverseengineering as well as other case studies in engineering. This book will be anideal reference for researchers, lecturers, graduates and engineers who areinterested in nature-inspired computation, artificial intelligence andcomputational intelligence. It can also serve as a reference for relevantcourses in computer science, artificial intelligence and machine learning, naturalcomputation, engineering optimization and data mining.

 

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

Dalla quarta di copertina

This timely review book summarizes thestate-of-the-art developments in nature-inspired optimization algorithms andtheir applications in engineering. Algorithms and topics include the overviewand history of nature-inspired algorithms, discrete firefly algorithm, discretecuckoo search, plant propagation algorithm, parameter-free bat algorithm,gravitational search, biogeography-based algorithm, differential evolution,particle swarm optimization and others. Applications include vehicle routing,swarming robots, discrete and combinatorial optimization, clustering ofwireless sensor networks, cell formation, economic load dispatch, metamodeling,surrogated-assisted cooperative co-evolution, data fitting and reverseengineering as well as other case studies in engineering. This book will be anideal reference for researchers, lecturers, graduates and engineers who areinterested in nature-inspired computation, artificial intelligence andcomputational intelligence. It can also serve as a reference for relevantcourses in computer science, artificial intelligence and machine learning, naturalcomputation, engineering optimization and data mining.

 

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

Altre edizioni note dello stesso titolo

9783319807577: Nature-Inspired Computation in Engineering: 637

Edizione in evidenza

ISBN 10:  3319807579 ISBN 13:  9783319807577
Casa editrice: Springer, 2018
Brossura