LEADER 04133nam 22007575 450 001 9910483527303321 005 20230329185701.0 010 $a3-319-41000-8 024 7 $a10.1007/978-3-319-41000-5 035 $a(CKB)3710000000735259 035 $a(DE-He213)978-3-319-41000-5 035 $a(MiAaPQ)EBC5587627 035 $a(Au-PeEL)EBL5587627 035 $a(OCoLC)952024108 035 $a(PPN)194378586 035 $a(EXLCZ)993710000000735259 100 $a20160614d2016 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAdvances in Swarm Intelligence $e7th International Conference, ICSI 2016, Bali, Indonesia, June 25-30, 2016, Proceedings, Part I /$fedited by Ying Tan, Yuhui Shi, Ben Niu 205 $a1st ed. 2016. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2016. 215 $a1 online resource (XXVII, 657 p. 193 illus.) 225 1 $aTheoretical Computer Science and General Issues,$x2512-2029 ;$v9712 311 $a3-319-40999-9 327 $aTrend and models of swarm intelligence research -- Novel swarm-based optimization algorithms.-Swarming behaviour -- Some swarm intelligence algorithms and their applications -- Hybrid search optimization -- Particle swarm optimization -- PSO applications -- Ant colony optimization -- Brain storm optimization -- Fireworks algorithms -- Multi-objective optimization -- Large-scale global optimization -- Biometrics. 330 $a This two-volume set LNCS 9712 and LNCS 9713 constitutes the refereed proceedings of the 7th International Conference on Swarm Intelligence, ICSI 2016, held in Bali, Indonesia, in June 2016. The 130 revised regular papers presented were carefully reviewed and selected from 231 submissions. The papers are organized in 22 cohesive sections covering major topics of swarm intelligence and related areas such as trend and models of swarm intelligence research; novel swarm-based optimization algorithms; swarming behaviour; some swarm intelligence algorithms and their applications; hybrid search optimization; particle swarm optimization; PSO applications; ant colony optimization; brain storm optimization; fireworks algorithms; multi-objective optimization; large-scale global optimization; biometrics; scheduling and planning; machine learning methods; clustering algorithm; classification; image classification and encryption; data mining; sensor networks and social networks; neural networks; swarm intelligence in management decision making and operations research; robot control; swarm robotics; intelligent energy and communications systems; and intelligent and interactive and tutoring systems. . 410 0$aTheoretical Computer Science and General Issues,$x2512-2029 ;$v9712 606 $aAlgorithms 606 $aArtificial intelligence 606 $aNumerical analysis 606 $aComputer science 606 $aData mining 606 $aComputer simulation 606 $aAlgorithms 606 $aArtificial Intelligence 606 $aNumerical Analysis 606 $aModels of Computation 606 $aData Mining and Knowledge Discovery 606 $aComputer Modelling 615 0$aAlgorithms. 615 0$aArtificial intelligence. 615 0$aNumerical analysis. 615 0$aComputer science. 615 0$aData mining. 615 0$aComputer simulation. 615 14$aAlgorithms. 615 24$aArtificial Intelligence. 615 24$aNumerical Analysis. 615 24$aModels of Computation. 615 24$aData Mining and Knowledge Discovery. 615 24$aComputer Modelling. 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 $aNiu$b Ben$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910483527303321 996 $aAdvances in Swarm Intelligence$92005634 997 $aUNINA