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008 171125s2018 gw | s |||| 0|eng d
020 _a9783662556634
_9978-3-662-55663-4
024 7 _a10.1007/978-3-662-55663-4
_2doi
050 4 _aTA352-356
050 4 _aQC20.7.N6
072 7 _aTBJ
_2bicssc
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_2thema
072 7 _aGPFC
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082 0 4 _a515.39
_223
245 1 0 _aEvolutionary Algorithms, Swarm Dynamics and Complex Networks
_h[electronic resource] :
_bMethodology, Perspectives and Implementation /
_cedited by Ivan Zelinka, Guanrong Chen.
250 _a1st ed. 2018.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2018.
300 _aXXII, 312 p. 194 illus., 155 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 _aEmergence, Complexity and Computation,
_x2194-7295 ;
_v26
520 _aEvolutionary algorithms constitute a class of well-known algorithms, which are designed based on the Darwinian theory of evolution and Mendelian theory of heritage. They are partly based on random and partly based on deterministic principles. Due to this nature, it is challenging to predict and control its performance in solving complex nonlinear problems. Recently, the study of evolutionary dynamics is focused not only on the traditional investigations but also on the understanding and analyzing new principles, with the intention of controlling and utilizing their properties and performances toward more effective real-world applications. In this book, based on many years of intensive research of the authors, is proposing novel ideas about advancing evolutionary dynamics towards new phenomena including many new topics, even the dynamics of equivalent social networks. In fact, it includes more advanced complex networks and incorporates them with the CMLs (coupled map lattices), which are usually used for spatiotemporal complex systems simulation and analysis, based on the observation that chaos in CML can be controlled, so does evolution dynamics. All the chapter authors are, to the best of our knowledge, originators of the ideas mentioned above and researchers on evolutionary algorithms and chaotic dynamics as well as complex networks, who will provide benefits to the readers regarding modern scientific research on related subjects. .
650 0 _aDynamics.
_948762
650 0 _aNonlinear theories.
_93339
650 0 _aGraph theory.
_93662
650 1 4 _aApplied Dynamical Systems.
_932005
650 2 4 _aGraph Theory.
_93662
700 1 _aZelinka, Ivan.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_948763
700 1 _aChen, Guanrong.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_948764
710 2 _aSpringerLink (Online service)
_948765
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783662556610
776 0 8 _iPrinted edition:
_z9783662556627
776 0 8 _iPrinted edition:
_z9783662572474
830 0 _aEmergence, Complexity and Computation,
_x2194-7295 ;
_v26
_948766
856 4 0 _uhttps://doi.org/10.1007/978-3-662-55663-4
912 _aZDB-2-ENG
912 _aZDB-2-SXE
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999 _c78284
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