LEADER 04150nam  22006975  450 
001 996465689603316
005 20230330022315.0
010   $a3-319-93815-0
024 7 $a10.1007/978-3-319-93815-8
035   $a(CKB)3810000000358685
035   $a(DE-He213)978-3-319-93815-8
035   $a(MiAaPQ)EBC6295168
035   $a(PPN)229494579
035   $a(EXLCZ)993810000000358685
100   $a20180615d2018      u|             0
101 0 $aeng
135   $aurnn|008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aAdvances in Swarm Intelligence$b[electronic resource] $e9th International Conference, ICSI 2018, Shanghai, China, June 17-22, 2018, Proceedings, Part I /$fedited by Ying Tan, Yuhui Shi, Qirong Tang
205   $a1st ed. 2018.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2018.
215   $a1 online resource (XXIV, 639 p. 183 illus.) 
225 1 $aTheoretical Computer Science and General Issues,$x2512-2029 ;$v10941
311   $a3-319-93814-2 
327   $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.
330   $aThe two-volume set of LNCS 10941 and 10942 constitutes the proceedings of the 9th International Conference on Advances in Swarm Intelligence, ICSI 2018, held in Shanghai, China, in June 2018. The total of 113 papers presented in these volumes was carefully reviewed and selected from 197 submissions. The papers were organized in topical sections as follows: theories and models of swarm intelligence; ant colony optimization; particle swarm optimization; artificial bee colony algorithms; genetic algorithms; differential evolution; fireworks algorithms; bacterial foraging optimization; artificial immune system; hydrologic cycle optimization; other swarm-based optimization algorithms; hybrid optimization algorithms; multi-objective optimization; large-scale global optimization; multi-agent systems; swarm robotics; fuzzy logic approaches; planning and routing problems; recommendation in social media; prediction, classification; finding patterns; image enhancement; deep learning. .
410  0$aTheoretical Computer Science and General Issues,$x2512-2029 ;$v10941
606   $aAlgorithms
606   $aArtificial intelligence
606   $aComputer networks
606   $aComputers, Special purpose
606   $aSoftware engineering
606   $aComputer science
606   $aAlgorithms
606   $aArtificial Intelligence
606   $aComputer Communication Networks
606   $aSpecial Purpose and Application-Based Systems
606   $aSoftware Engineering
606   $aModels of Computation
615  0$aAlgorithms.
615  0$aArtificial intelligence.
615  0$aComputer networks.
615  0$aComputers, Special purpose.
615  0$aSoftware engineering.
615  0$aComputer science.
615 14$aAlgorithms.
615 24$aArtificial Intelligence.
615 24$aComputer Communication Networks.
615 24$aSpecial Purpose and Application-Based Systems.
615 24$aSoftware Engineering.
615 24$aModels of Computation.
676   $a005.1
702   $aTan$b Ying$4edt$4http://id.loc.gov/vocabulary/relators/edt
702   $aShi$b Yuhui$4edt$4http://id.loc.gov/vocabulary/relators/edt
702   $aTang$b Qirong$4edt$4http://id.loc.gov/vocabulary/relators/edt
906   $aBOOK
912   $a996465689603316
996   $aAdvances in Swarm Intelligence$92005634
997   $aUNISA