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020 _a9783319281612
040 _aES-MaUEC
050 4 _aQ342
_b.S454 2016
082 0 4 _a006.3
245 1 0 _aSelf-Organizing Migrating Algorithm :
_bMethodology and Implementation
_cedited by Donald Davendra, Ivan Zelinka
250 _a1st ed.
260 _aCham
_bSpringer International Publishing
_c2016
300 _a1 recurso en línea (XVIII, 289 páginas)
_b128 ilustraciones, 41 ilustraciones en color
336 _aTexto
_btxt
_2rdacontent
337 _aelectrónico
_bc
_2rdamedia
338 _arecurso electrónico
_bcr
_2rdacarrier
490 0 _aStudies in Computational Intelligence
_x1860-949X
_v626
520 3 _aThis book brings together the current state of-the-art research in Self Organizing Migrating Algorithm (SOMA) as a novel population-based evolutionary algorithm, modeled on the predator-prey relationship, by its leading practitioners. As the first ever book on SOMA, this book is geared towards graduate students, academics and researchers, who are looking for a good optimization algorithm for their applications. This book presents the methodology of SOMA, covering both the real and discrete domains, and its various implementations in different research areas. The easy-to-follow and implement methodology used in the book will make it easier for a reader to implement, modify and utilize SOMA. .
710 2 _aSpringerLink (Online service)
_0Local
_9106996
942 _2lcc
_cLE
988 _aEBOOK, asignarmaterias , EBSPRINGER
650 7 _aInteligencia artificial
_0comprobar BNE19900997218
_2embne
_9413115
650 7 _9145705
_aOptimización matemática
_0comprobar BNE19922522034
_2embne
700 1 _aDavendra, Donald
_eeditor literario
_0Local
_998365
700 1 _aZelinka, Ivan.
_eeditor literario
_998164
_0Local
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-3-319-28161-2
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
901 _ai9783319281612
907 _a.b12947003
_b10-10-17
_c21-11-16
998 _am
_a_alco
_a_vill
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