LEADER 04068nam  22007335  450 
001 9910483513103321
005 20230329185719.0
010   $a3-319-41009-1
024 7 $a10.1007/978-3-319-41009-8
035   $a(CKB)3710000000735260
035   $a(DE-He213)978-3-319-41009-8
035   $a(MiAaPQ)EBC5594571
035   $a(PPN)194378594
035   $a(EXLCZ)993710000000735260
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 $e7th International Conference, ICSI 2016, Bali, Indonesia, June 25-30, 2016, Proceedings, Part II /$fedited by Ying Tan, Yuhui Shi, Li Li
205   $a1st ed. 2016.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2016.
215   $a1 online resource (XXVII, 629 p. 260 illus.)
225 1 $aTheoretical Computer Science and General Issues,$x2512-2029 ;$v9713
311   $a3-319-41008-3 
327   $aScheduling 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 -- Intelligent and interactive and tutoring systems. .
330   $aThis two-volume set LNCS 9712 and LNCS 9713 constitutes the refereed proceedings of the 7th International Conference on Swarm Intelligence, ICSI 2016, held in Bali, Indonesia, in June 2016. The 130 revised regular papers presented were carefully reviewed and selected from 231 submissions. The papers are organized in 22 cohesive sections covering major topics of swarm intelligence and related areas such as trend and models of swarm intelligence research; novel swarm-based optimization algorithms; swarming behaviour; some swarm intelligence algorithms and their applications; hybrid search optimization; particle swarm optimization; PSO applications; ant colony optimization; brain storm optimization; fireworks algorithms; multi-objective optimization; large-scale global optimization; biometrics; scheduling and planning; machine learning methods; clustering algorithm; classification; image classification and encryption; data mining; sensor networks and social networks; neural networks; swarm intelligence in management decision making and operations research; robot control; swarm robotics; intelligent energy and communications systems; and intelligent and interactive and tutoring systems. .
410  0$aTheoretical Computer Science and General Issues,$x2512-2029 ;$v9713
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   $a006.3824
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   $aLi$b Li$4edt$4http://id.loc.gov/vocabulary/relators/edt
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910483513103321
996   $aAdvances in Swarm Intelligence$92005634
997   $aUNINA