Advances in Swarm Intelligence [electronic resource] : 9th International Conference, ICSI 2018, Shanghai, China, June 17-22, 2018, Proceedings, Part II / edited by Ying Tan, Yuhui Shi, Qirong Tang.

Colaborador(es): Tan, Ying [editor.] | Shi, Yuhui [editor.] | Tang, Qirong [editor.] | SpringerLink (Online service)Tipo de material: TextoTextoSeries Theoretical Computer Science and General Issues ; 10942Editor: Cham : Springer International Publishing : Imprint: Springer, 2018Edición: 1st ed. 2018Descripción: XXIV, 579 p. 247 illus. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783319938189Tema(s): Algorithms | Artificial intelligence | Computers | Computer organization | Algorithm Analysis and Problem Complexity | Artificial Intelligence | Information Systems and Communication Service | Computer Systems Organization and Communication NetworksFormatos físicos adicionales: Printed edition:: Sin título; Printed edition:: Sin títuloClasificación CDD: 005.1 Clasificación LoC:QA76.9.A43Recursos en línea: Libro electrónicoTexto
Contenidos:
Multi-agent systems -- swarm robotics -- fuzzy logic approaches -- planning and routing problems -- recommendation in social media -- predication -- classification -- finding patterns -- image enhancement -- deep learning -- theories and models of swarm intelligence -- ant colony optimization -- particle swarm optimization -- artificial bee colony algorithms -- genetic algorithms -- differential evolution -- fireworks algorithm -- bacterial foraging optimization -- artificial immune system -- hydrologic cycle optimization -- other swarm-based optimization algorithms -- hybrid optimization algorithms -- multi-objective optimization -- large-scale global optimization. .
En: Springer Nature eBookResumen: The two-volume set of LNCS 10941 and 10942 constitutes the proceedings of the 9th International Conference on Advances in Swarm Intelligence, ICSI 2018, held in Shanghai, China, in June 2018. The total of 113 papers presented in these volumes was carefully reviewed and selected from 197 submissions. The papers were organized in topical sections namely: multi-agent systems; swarm robotics; fuzzy logic approaches; planning and routing problems; recommendation in social media; predication; classification; finding patterns; image enhancement; deep learning; theories and models of swarm intelligence; ant colony optimization; particle swarm optimization; artificial bee colony algorithms; genetic algorithms; differential evolution; fireworks algorithm; bacterial foraging optimization; artificial immune system; hydrologic cycle optimization; other swarm-based optimization algorithms; hybrid optimization algorithms; multi-objective optimization; large-scale global optimization.
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Multi-agent systems -- swarm robotics -- fuzzy logic approaches -- planning and routing problems -- recommendation in social media -- predication -- classification -- finding patterns -- image enhancement -- deep learning -- theories and models of swarm intelligence -- ant colony optimization -- particle swarm optimization -- artificial bee colony algorithms -- genetic algorithms -- differential evolution -- fireworks algorithm -- bacterial foraging optimization -- artificial immune system -- hydrologic cycle optimization -- other swarm-based optimization algorithms -- hybrid optimization algorithms -- multi-objective optimization -- large-scale global optimization. .

The two-volume set of LNCS 10941 and 10942 constitutes the proceedings of the 9th International Conference on Advances in Swarm Intelligence, ICSI 2018, held in Shanghai, China, in June 2018. The total of 113 papers presented in these volumes was carefully reviewed and selected from 197 submissions. The papers were organized in topical sections namely: multi-agent systems; swarm robotics; fuzzy logic approaches; planning and routing problems; recommendation in social media; predication; classification; finding patterns; image enhancement; deep learning; theories and models of swarm intelligence; ant colony optimization; particle swarm optimization; artificial bee colony algorithms; genetic algorithms; differential evolution; fireworks algorithm; bacterial foraging optimization; artificial immune system; hydrologic cycle optimization; other swarm-based optimization algorithms; hybrid optimization algorithms; multi-objective optimization; large-scale global optimization.

UABC ; Temporal ; 01/01/2021-12/31/2023.

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