000 03180nam a22004815i 4500
001 978-3-319-14400-9
003 DE-He213
005 20200421111842.0
007 cr nn 008mamaa
008 150124s2015 gw | s |||| 0|eng d
020 _a9783319144009
_9978-3-319-14400-9
024 7 _a10.1007/978-3-319-14400-9
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
245 1 0 _aAdaptation and Hybridization in Computational Intelligence
_h[electronic resource] /
_cedited by Iztok Fister, Iztok Fister Jr.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2015.
300 _aX, 237 p. 42 illus., 1 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aAdaptation, Learning, and Optimization,
_x1867-4534 ;
_v18
505 0 _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.
520 _a  This 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.  .
650 0 _aEngineering.
650 0 _aArtificial intelligence.
650 0 _aComputational intelligence.
650 1 4 _aEngineering.
650 2 4 _aComputational Intelligence.
650 2 4 _aArtificial Intelligence (incl. Robotics).
700 1 _aFister, Iztok.
_eeditor.
700 1 _aFister Jr., Iztok.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319143996
830 0 _aAdaptation, Learning, and Optimization,
_x1867-4534 ;
_v18
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-14400-9
912 _aZDB-2-ENG
942 _cEBK
999 _c55590
_d55590