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Advances in Swarm Intelligence - Ying Tan - Bog

Bag om Advances in Swarm Intelligence

This two-volume set LNCS 13344 and 13345 constitutes the proceedings of the 13th International Conference on Advances in Swarm Intelligence, ICSI 2022, which took place in Xi¿an, China, in July 2022. The theme of this year¿s conference was ¿Serving Life with Swarm Intelligence¿. The 85 full papers presented were carefully reviewed and selected from 171 submissions. The papers of the second part cover topics such as: Swarm Robotics and Multi-agent System; Deep Neural Networks; Machine Learning; Data Mining; Other Optimization Applications; ICSI-OC¿2022: Competition on Single Objective Bounded Optimization Problems; Swarm Intelligence and Nature-Inspired Computing; Swarm-based Computing Algorithms for Optimization; Particle Swarm Optimization; Ant Colony Optimization; Genetic Algorithm and Evolutionary Computation; Fireworks Algorithms; Brain Storm Optimization Algorithm; Swarm Intelligence Approach-based Applications; Multi-Objective Optimization.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9783031097256
  • Indbinding:
  • Paperback
  • Sideantal:
  • 476
  • Udgivet:
  • 26. juni 2022
  • Udgave:
  • 22001
  • Størrelse:
  • 155x26x235 mm.
  • Vægt:
  • 715 g.
  • 8-11 hverdage.
  • 16. januar 2025
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Forlænget returret til d. 31. januar 2025
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Beskrivelse af Advances in Swarm Intelligence

This two-volume set LNCS 13344 and 13345 constitutes the proceedings of the 13th International Conference on Advances in Swarm Intelligence, ICSI 2022, which took place in Xi¿an, China, in July 2022. The theme of this year¿s conference was ¿Serving Life with Swarm Intelligence¿.
The 85 full papers presented were carefully reviewed and selected from 171 submissions. The papers of the second part cover topics such as: Swarm Robotics and Multi-agent System; Deep Neural Networks; Machine Learning; Data Mining; Other Optimization Applications; ICSI-OC¿2022: Competition on Single Objective Bounded Optimization Problems; Swarm Intelligence and Nature-Inspired Computing; Swarm-based Computing Algorithms for Optimization; Particle Swarm Optimization; Ant Colony Optimization; Genetic Algorithm and Evolutionary Computation; Fireworks Algorithms; Brain Storm Optimization Algorithm; Swarm Intelligence Approach-based Applications; Multi-Objective Optimization.

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