04608nam 22008175 450 99620252500331620230329153507.03-319-11897-810.1007/978-3-319-11897-0(CKB)3710000000228653(SSID)ssj0001354030(PQKBManifestationID)11768662(PQKBTitleCode)TC0001354030(PQKBWorkID)11316909(PQKB)11648615(DE-He213)978-3-319-11897-0(MiAaPQ)EBC6286507(MiAaPQ)EBC5595165(Au-PeEL)EBL5595165(OCoLC)1076243226(PPN)181352230(EXLCZ)99371000000022865320140903d2014 u| 0engurnn#008mamaatxtccrAdvances in Swarm Intelligence[electronic resource] 5th International Conference, ICSI 2014, Hefei, China, October 17-20, 2014, Proceedings, Part II /edited by Ying Tan, Yuhui Shi, Carlos A Coello Coello1st ed. 2014.Cham :Springer International Publishing :Imprint: Springer,2014.1 online resource (XXIV, 466 p. 163 illus.)Theoretical Computer Science and General Issues,2512-2029 ;8795Includes index.3-319-11896-X 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.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.Theoretical Computer Science and General Issues,2512-2029 ;8795AlgorithmsNumerical analysisComputer science—MathematicsDiscrete mathematicsData miningArtificial intelligenceAlgorithmsNumerical AnalysisDiscrete Mathematics in Computer ScienceData Mining and Knowledge DiscoveryArtificial IntelligenceAlgorithms.Numerical analysis.Computer science—Mathematics.Discrete mathematics.Data mining.Artificial intelligence.Algorithms.Numerical Analysis.Discrete Mathematics in Computer Science.Data Mining and Knowledge Discovery.Artificial Intelligence.004Tan Yingedthttp://id.loc.gov/vocabulary/relators/edtShi Yuhuiedthttp://id.loc.gov/vocabulary/relators/edtCoello Coello Carlos Aedthttp://id.loc.gov/vocabulary/relators/edtMiAaPQMiAaPQMiAaPQBOOK996202525003316Advances in Swarm Intelligence2005634UNISA