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Nature-Inspired Computation in Engineering: Studies in Computational Intelligence, cartea 637

Editat de Xin She Yang
en Limba Engleză Hardback – 30 mar 2016
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.
 
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Specificații

ISBN-13: 9783319302331
ISBN-10: 3319302337
Pagini: 276
Ilustrații: X, 276 p. 54 illus., 34 illus. in color.
Dimensiuni: 155 x 235 x 18 mm
Greutate: 0.58 kg
Ediția:1st ed. 2016
Editura: Springer International Publishing
Colecția Springer
Seria Studies in Computational Intelligence

Locul publicării:Cham, Switzerland

Cuprins

Flower Pollination Algorithm and its Applications in Engineering.- An Evolutionary Discrete Firefly Algorithm with
Novel Operators for Solving the Vehicle Routing Problem with TimeWindows.- The Plant Propagation Algorithm for Discrete Optimisation: The Case of the Travelling Salesman Problem.- Enhancing Cooperative Coevolution with Surrogate-Assisted Local Search.- Cuckoo Search: From Cuckoo Reproduction Strategy to CombinatorialOptimization.- Clustering Optimization for WSN based on Nature-Inspired Algorithms.- Discrete Firefly Algorithm for Recruiting Task in a Swarm of Robots.- Nature-Inspired Swarm Intelligence for Data Fitting in Reverse Engineering: Recent Advances and FutureTrends.- A Novel Fast Optimisation Algorithm Using Differential Evolution Algorithm Optimisation and Meta-
Modelling Approach.- A Hybridization of Runner-Based and Seed-Based Plant PropagationAlgorithm.- Gravitational Search Algorithm Applied to Cell Formation Problem.- Parameterless Bat Algorithm and its Performace Study.

Textul de pe ultima copertă

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.
 

Caracteristici

Provides a timely review and summary of the latest
developments of nature-inspired computation and their diverse applications in
Reviews both theoretical studies and applications
Focuses on diverse applications and detaileddescriptions of algorithms and backgrounds
Includes supplementary material: sn.pub/extras