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000725375 020__ $$a9783319144009$$qelectronic book
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000725375 0247_ $$a10.1007/978-3-319-14400-9$$2doi
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000725375 24500 $$aAdaptation and hybridization in computational intelligence$$h[electronic resource] /$$cIztok Fister, Iztok Fister Jr., editors.
000725375 264_1 $$aCham [Switzerland] :$$bSpringer,$$c2015.
000725375 300__ $$a1 online resource.
000725375 336__ $$atext$$btxt$$2rdacontent
000725375 337__ $$acomputer$$bc$$2rdamedia
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000725375 4901_ $$aAdaptation, learning, and optimization ;$$vvolume 18
000725375 504__ $$aIncludes bibliographical references and index.
000725375 5050_ $$aAdaptation and Hybridization in Nature-Inspired Algorithms -- Adaptation in the Differential Evolution -- On the Mutation Operators in Evolution Strategies -- Adaptation in Cooperative Coevolutionary Optimization -- Study of Lagrangian and Evolutionary Parameters in Krill Herd Algorithm -- Solutions of Non-Smooth Economic Dispatch Problems by Swarm Intelligence -- Hybrid Artifcial Neural Network for Fire Analysis of Steel Frames -- A Differential Evolution Algorithm with A Variable Neighborhood Search for Constrained Function Optimization -- A Memetic Differential Evolution Algorithm for the Vehicle Routing Problem with Stochastic Demands.
000725375 506__ $$aAccess limited to authorized users.
000725375 520__ $$aThis carefully edited book takes a walk through recent advances in adaptation and hybridization in the Computational Intelligence (CI) domain. It consists of ten chapters that are divided into three parts. The first part illustrates background information and provides some theoretical foundation tackling the CI domain, the second part deals with the adaptation in CI algorithms, while the third part focuses on the hybridization in CI. This book can serve as an ideal reference for researchers and students of computer science, electrical and civil engineering, economy, and natural sciences that are confronted with solving the optimization, modeling and simulation problems. It covers the recent advances in CI that encompass Nature-inspired algorithms, like Artificial Neural networks, Evolutionary Algorithms and Swarm Intelligence ?based algorithms.
000725375 650_0 $$aComputational intelligence.
000725375 7001_ $$aFister, Iztok,$$eeditor.
000725375 7001_ $$aFister, Iztok,$$bJr.,$$eeditor.
000725375 77608 $$iPrint version:$$z9783319143996
000725375 830_0 $$aAdaptation. learning and optimization ;$$vvolume 18.
000725375 852__ $$bebk
000725375 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-14400-9$$zOnline Access$$91397441.1
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000725375 980__ $$aEBOOK
000725375 980__ $$aBIB
000725375 982__ $$aEbook
000725375 983__ $$aOnline
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