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020 _a9783319118574
_9978-3-319-11857-4
024 7 _a10.1007/978-3-319-11857-4
_2doi
050 4 _aQA76.9.A43
072 7 _aUMB
_2bicssc
072 7 _aCOM051300
_2bisacsh
072 7 _aUMB
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082 0 4 _a518.1
_223
245 1 0 _aAdvances in Swarm Intelligence
_h[electronic resource] :
_b5th International Conference, ICSI 2014, Hefei, China, October 17-20, 2014, Proceedings, Part I /
_cedited by Ying Tan, Yuhui Shi, Carlos Coello Coello.
250 _a1st ed. 2014.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2014.
300 _aXXIV, 510 p. 162 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 ;
_v8794
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 _aAlgorithms.
_93390
650 0 _aNumerical analysis.
_94603
650 0 _aComputer science
_xMathematics.
_93866
650 0 _aDiscrete mathematics.
_912873
650 0 _aData mining.
_93907
650 0 _aArtificial intelligence.
_93407
650 1 4 _aAlgorithms.
_93390
650 2 4 _aNumerical Analysis.
_94603
650 2 4 _aDiscrete Mathematics in Computer Science.
_931837
650 2 4 _aData Mining and Knowledge Discovery.
_991771
650 2 4 _aArtificial Intelligence.
_93407
700 1 _aTan, Ying.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_991772
700 1 _aShi, Yuhui.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_991773
700 1 _aCoello Coello, Carlos.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_991774
710 2 _aSpringerLink (Online service)
_991775
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319118567
776 0 8 _iPrinted edition:
_z9783319118581
830 0 _aTheoretical Computer Science and General Issues,
_x2512-2029 ;
_v8794
_991776
856 4 0 _uhttps://doi.org/10.1007/978-3-319-11857-4
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