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001 978-3-319-11897-0
003 DE-He213
005 20200421111208.0
007 cr nn 008mamaa
008 140903s2014 gw | s |||| 0|eng d
020 _a9783319118970
_9978-3-319-11897-0
024 7 _a10.1007/978-3-319-11897-0
_2doi
050 4 _aQA76.9.A43
072 7 _aUMB
_2bicssc
072 7 _aCOM051300
_2bisacsh
082 0 4 _a005.1
_223
245 1 0 _aAdvances in Swarm Intelligence
_h[electronic resource] :
_b5th International Conference, ICSI 2014, Hefei, China, October 17-20, 2014, Proceedings, Part II /
_cedited by Ying Tan, Yuhui Shi, Carlos A. Coello Coello.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2014.
300 _aXXIV, 466 p. 163 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Computer Science,
_x0302-9743 ;
_v8795
505 0 _aNovel swarm-based search methods -- Novel optimization algorithm -- Particle swarm optimization -- Ant colony optimization for travelling salesman problem -- Artificial bee colony algorithms -- Artificial immune system -- Evolutionary algorithms -- Neural networks and fuzzy methods -- Hybrid methods -- Multi-objective optimization -- Multi-agent systems -- Evolutionary clustering algorithms -- Classification methods -- GPU-based methods -- Scheduling and path planning -- Wireless sensor networks -- Power system optimization -- Swarm intelligence in image and video processing -- Applications of swarm intelligence to management problems -- Swarm intelligence for real-world application.
520 _aThis book and its companion volume, LNCS vol. 8794 and 8795 constitute the proceedings of the 5th International Conference on Swarm Intelligence, ICSI 2014, held in Hefei, China in October 2014. The 107 revised full papers presented were carefully reviewed and selected from 198 submissions. The papers are organized in 18 cohesive sections, 3 special sessions and one competitive session covering all major topics of swarm intelligence research and development such as novel swarm-based search methods; novel optimization algorithm; particle swarm optimization; ant colony optimization for travelling salesman problem; artificial bee colony algorithms; artificial immune system; evolutionary algorithms; neural networks and fuzzy methods; hybrid methods; multi-objective optimization; multi-agent systems; evolutionary clustering algorithms; classification methods; GPU-based methods; scheduling and path planning; wireless sensor networks; power system optimization; swarm intelligence in image and video processing; applications of swarm intelligence to management problems; swarm intelligence for real-world application.
650 0 _aComputer science.
650 0 _aAlgorithms.
650 0 _aNumerical analysis.
650 0 _aComputer science
_xMathematics.
650 0 _aData mining.
650 0 _aArtificial intelligence.
650 1 4 _aComputer Science.
650 2 4 _aAlgorithm Analysis and Problem Complexity.
650 2 4 _aNumeric Computing.
650 2 4 _aDiscrete Mathematics in Computer Science.
650 2 4 _aData Mining and Knowledge Discovery.
650 2 4 _aArtificial Intelligence (incl. Robotics).
700 1 _aTan, Ying.
_eeditor.
700 1 _aShi, Yuhui.
_eeditor.
700 1 _aCoello, Carlos A. Coello.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319118963
830 0 _aLecture Notes in Computer Science,
_x0302-9743 ;
_v8795
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-11897-0
912 _aZDB-2-SCS
912 _aZDB-2-LNC
942 _cEBK
999 _c54242
_d54242