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Titlebook: Advances in Swarm Intelligence; 4th International Co Ying Tan,Yuhui Shi,Hongwei Mo Conference proceedings 2013 Springer-Verlag Berlin Heide

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31#
發(fā)表于 2025-3-26 22:44:42 | 只看該作者
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發(fā)表于 2025-3-27 02:11:25 | 只看該作者
Local and Global Search Based PSO Algorithm experience, which is the same as the standard PSO. Simulation results and comparisons with the standard PSO 2007 demonstrate that the proposed algorithm effectively enhances searching efficiency and improves the quality of searching.
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發(fā)表于 2025-3-27 06:23:50 | 只看該作者
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發(fā)表于 2025-3-27 17:34:34 | 只看該作者
https://doi.org/10.1007/978-3-658-03097-1rithms have been simulated and compared with the particle swarm optimization and the simple particle swarm optimization. The simulations show that the algorithms have a higher convergence precision for some functions or a particular issue.
36#
發(fā)表于 2025-3-27 21:02:11 | 只看該作者
https://doi.org/10.1007/978-3-642-38703-6applications; design; graphs; machine learning; optimization algorithms; algorithm analysis and problem c
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發(fā)表于 2025-3-27 23:37:47 | 只看該作者
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發(fā)表于 2025-3-28 03:29:57 | 只看該作者
Joachim Hereth Correia,Tim B. Kaiser enables us to examine collective behaviors in fish shoals. The system uses small wheeled robots, moving under a water tank. The robots are coupled to a fish replica inside the tank using neodymium magnets. The position of the robots and each fish in the swarm is tracked by two cameras. The robots c
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發(fā)表于 2025-3-28 07:58:14 | 只看該作者
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