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|a 9783319118574
|9 978-3-319-11857-4
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|a 10.1007/978-3-319-11857-4
|2 doi
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|a QA76.9.A43
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|a Advances in Swarm Intelligence
|h [electronic resource] :
|b 5th International Conference, ICSI 2014, Hefei, China, October 17-20, 2014, Proceedings, Part I /
|c edited by Ying Tan, Yuhui Shi, Carlos Coello Coello.
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|a 1st ed. 2014.
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2014.
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|a XXIV, 510 p. 162 illus.
|b online resource.
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|a text
|b txt
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|a computer
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|a online resource
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|b PDF
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|a Theoretical Computer Science and General Issues ;
|v 8794
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|a 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.
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|a This 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.
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|a Algorithms.
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|a Numerical analysis.
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|a Computer science—Mathematics.
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|a Data mining.
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|a Artificial intelligence.
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|a Algorithm Analysis and Problem Complexity.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/I16021
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|a Numeric Computing.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/I1701X
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|a Discrete Mathematics in Computer Science.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/I17028
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|a Data Mining and Knowledge Discovery.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/I18030
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|a Artificial Intelligence.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/I21000
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|a Tan, Ying.
|e editor.
|0 (orcid)0000-0001-8243-4731
|1 https://orcid.org/0000-0001-8243-4731
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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|a Shi, Yuhui.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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|a Coello Coello, Carlos.
|e editor.
|0 (orcid)0000-0002-8435-680X
|1 https://orcid.org/0000-0002-8435-680X
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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|a SpringerLink (Online service)
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|t Springer Nature eBook
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|i Printed edition:
|z 9783319118581
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|i Printed edition:
|z 9783319118567
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|a Theoretical Computer Science and General Issues ;
|v 8794
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|u https://doi.org/10.1007/978-3-319-11857-4
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|a ZDB-2-SCS
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|a ZDB-2-SXCS
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|a ZDB-2-LNC
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|a Computer Science (SpringerNature-11645)
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|a Computer Science (R0) (SpringerNature-43710)
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