Download e-book for iPad: Advances in Swarm Intelligence: 5th International by Ying Tan, Yuhui Shi, Carlos Coello Coello

By Ying Tan, Yuhui Shi, Carlos Coello Coello

ISBN-10: 3319118560

ISBN-13: 9783319118567

ISBN-10: 3319118579

ISBN-13: 9783319118574

This ebook and its better half quantity, LNCS vol. 8794 and 8795 represent the complaints of the fifth foreign convention on Swarm Intelligence, ICSI 2014, held in Hefei, China in October 2014. The 107 revised complete papers provided have been rigorously reviewed and chosen from 198 submissions. The papers are prepared in 18 cohesive sections, three targeted classes and one aggressive consultation masking all significant issues of swarm intelligence study and improvement equivalent to novel swarm-based seek tools; novel optimization set of rules; particle swarm optimization; ant colony optimization for vacationing salesman challenge; synthetic bee colony algorithms; man made immune method; evolutionary algorithms; neural networks and fuzzy equipment; hybrid tools; multi-objective optimization; multi-agent platforms; evolutionary clustering algorithms; type tools; GPU-based tools; scheduling and course making plans; instant sensor networks; strength process optimization; swarm intelligence in snapshot and video processing; functions of swarm intelligence to administration difficulties; swarm intelligence for real-world application.

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Additional resources for Advances in Swarm Intelligence: 5th International Conference, ICSI 2014, Hefei, China, October 17-20, 2014, Proceedings, Part I

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That is to say, X Ki took the initiative to diminish the Euclidean distance with X Kbest . , G Ki = G Ki + λ ( G Kb e s t − G Ki ) (4) Wherein, λ ∈ [0,1] , stands for the shift step length of individual X Ki . It seems that there is no difference between external benchmarking learning and internal benchmarking learning, because they are all apt to narrow the Hamming (or Euclidean) distance between an individual and the best one. As a matter of fact, there is great difference between external and internal benchmarking learning.

Understanding Crowd Behaviours, Cabinet Office Emergency Planning College (2009) 18. : Agent-based modeling: Methods and techniques for simulating human systems. Proceedings of the National Academy of Sciences of the United States of America 99(Suppl. 3), 7280–7287 (2002) 18 O. Beltaief, S. El Hadouaj, and K. Ghedira 19. : The big five versus the big four: The relationship between the Myers-Briggs Type Indicator (MBTI) and NEO-PI five factor model of personality. Personality and Individual Differences (1996) 20.

The macroscopic approaches simulate the behavior of the crowd as a whole. In fact, macroscopic models don't consider individual features such as physical abilities, direction of movement, and individual positioning [16]. This causes a lack of realism [17]. On the other hand, the microscopic approaches are interested in the behavior, actions and decisions of each pedestrian and his interaction with others [17]. Therefore, the microscopic models allow us to obtain more realistic simulations. For this reason, in our work, we adopt a microscopic approach and more specifically an agent-based model.

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Advances in Swarm Intelligence: 5th International Conference, ICSI 2014, Hefei, China, October 17-20, 2014, Proceedings, Part I by Ying Tan, Yuhui Shi, Carlos Coello Coello

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