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001 978-3-319-93815-8
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020 _a9783319938158
_9978-3-319-93815-8
024 7 _a10.1007/978-3-319-93815-8
_2doi
050 4 _aQA76.9.A43
072 7 _aUMB
_2bicssc
072 7 _aCOM051300
_2bisacsh
072 7 _aUMB
_2thema
082 0 4 _a518.1
_223
245 1 0 _aAdvances in Swarm Intelligence
_h[electronic resource] :
_b9th International Conference, ICSI 2018, Shanghai, China, June 17-22, 2018, Proceedings, Part I /
_cedited by Ying Tan, Yuhui Shi, Qirong Tang.
250 _a1st ed. 2018.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2018.
300 _aXXIV, 639 p. 183 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aTheoretical Computer Science and General Issues,
_x2512-2029 ;
_v10941
505 0 _aTheories and models of swarm intelligence -- ant colony optimization; particle swarm optimization -- artificial bee colony algorithms -- genetic algorithms -- differential evolution -- fireworks algorithms -- bacterial foraging optimization -- artificial immune system -- hydrologic cycle optimization -- other swarm-based optimization algorithms -- hybrid optimization algorithms -- multi-objective optimization -- large-scale global optimization -- multi-agent systems -- swarm robotics; fuzzy logic approaches -- planning and routing problems -- recommendation in social media -- prediction -- classification -- finding patterns -- image enhancement -- deep learning.
520 _aThe two-volume set of LNCS 10941 and 10942 constitutes the proceedings of the 9th International Conference on Advances in Swarm Intelligence, ICSI 2018, held in Shanghai, China, in June 2018. The total of 113 papers presented in these volumes was carefully reviewed and selected from 197 submissions. The papers were organized in topical sections as follows: theories and models of swarm intelligence; ant colony optimization; particle swarm optimization; artificial bee colony algorithms; genetic algorithms; differential evolution; fireworks algorithms; bacterial foraging optimization; artificial immune system; hydrologic cycle optimization; other swarm-based optimization algorithms; hybrid optimization algorithms; multi-objective optimization; large-scale global optimization; multi-agent systems; swarm robotics; fuzzy logic approaches; planning and routing problems; recommendation in social media; prediction, classification; finding patterns; image enhancement; deep learning. .
650 0 _aAlgorithms.
_93390
650 0 _aArtificial intelligence.
_93407
650 0 _aComputer networks .
_931572
650 0 _aComputers, Special purpose.
_946653
650 0 _aSoftware engineering.
_94138
650 0 _aComputer science.
_99832
650 1 4 _aAlgorithms.
_93390
650 2 4 _aArtificial Intelligence.
_93407
650 2 4 _aComputer Communication Networks.
_9127486
650 2 4 _aSpecial Purpose and Application-Based Systems.
_946654
650 2 4 _aSoftware Engineering.
_94138
650 2 4 _aModels of Computation.
_931806
700 1 _aTan, Ying.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9127487
700 1 _aShi, Yuhui.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9127488
700 1 _aTang, Qirong.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9127489
710 2 _aSpringerLink (Online service)
_9127490
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319938141
776 0 8 _iPrinted edition:
_z9783319938165
830 0 _aTheoretical Computer Science and General Issues,
_x2512-2029 ;
_v10941
_9127491
856 4 0 _uhttps://doi.org/10.1007/978-3-319-93815-8
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
912 _aZDB-2-LNC
942 _cELN
999 _c91263
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