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Record Nr. |
UNINA9910483745103321 |
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Titolo |
Advances in Swarm Intelligence : 4th International Conference, ICSI 2013, Harbin, China, June 12-15, 2013, Proceedings, Part I / / edited by Ying Tan, Yuhui Shi, Hongwei Mo |
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Pubbl/distr/stampa |
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Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2013 |
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ISBN |
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Edizione |
[1st ed. 2013.] |
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Descrizione fisica |
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1 online resource (XXII, 576 p. 197 illus.) |
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Collana |
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Theoretical Computer Science and General Issues, , 2512-2029 ; ; 7928 |
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Disciplina |
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Soggetti |
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Algorithms |
Numerical analysis |
Computer science - Mathematics |
Discrete mathematics |
Data mining |
Artificial intelligence |
Numerical Analysis |
Discrete Mathematics in Computer Science |
Data Mining and Knowledge Discovery |
Artificial Intelligence |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Bibliographic Level Mode of Issuance: Monograph |
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Nota di contenuto |
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Analysis of Swarm Intelligence Based Algorithms -- Particle Swarm Optimization -- Applications of PSO Algorithms -- Ant Colony Optimization Algorithms.- Biogeography-Based Optimization Algorithms -- Novel Swarm-Based Search Methods -- Bee Colony Algorithms -- Differential Evolution -- Parameter Optimization -- Neural Networks -- Fuzzy Methods -- Evolutionary Programming and Evolutionary Games. |
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Sommario/riassunto |
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This book and its companion volume, LNCS vols. 7928 and 7929 constitute the proceedings of the 4th International Conference on Swarm Intelligence, ICSI 2013, held in Harbin, China in June 2013. The 129 revised full papers presented were carefully reviewed and selected from 268 submissions. The papers are organized in 22 cohesive |
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sections covering all major topics of swarm intelligence research and developments. The following topics are covered in this volume: analysis of swarm intelligence based algorithms, particle swarm optimization, applications of particle swarm optimization algorithms, ant colony optimization algorithms, biogeography-based optimization algorithms, novel swarm-based search methods, bee colony algorithms, differential evolution, neural networks, fuzzy methods, evolutionary programming and evolutionary games. |
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