Particle Swarm Optimization Using Levy Probability Distribution

机译：基于征税概率分布的粒子群算法

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Velocity threshold is an important parameter to affect the performance of particle swarm optimization. In this paper, a novel velocity threshold automation strategy is proposed by incorporated with Levy probability distribution. Different from Gaussian and Cauchy distribution, it has an infinite second moment and is likely to generate an offspring that is far away from its parent. Therefore, this method employs a larger capability of the global exploration by providing a large velocity scale for each particle. Simulation results show the proposed strategy is effective and efficient.

机译：速度阈值是影响粒子群优化性能的重要参数。结合Levy概率分布，提出了一种新的速度阈值自动化策略。与高斯和柯西分布不同，它具有无限的第二矩，并且很可能产生远离其父代的后代。因此，该方法通过为每个粒子提供较大的速度范围，从而具有更大的全局探测能力。仿真结果表明该策略是有效的。

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来源
《International Symposium on Intelligence Computation amp; Applications(ISICA'2007); 20070921-23; Wuhan(CN)》|2007年|P.353-361|共9页
会议地点 Wuhan(CN)
作者
Xingjuan Cai; Jianchao Zeng; Zhihua Cui; Ying Tan;
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作者单位

Division of system simulation and computer application, Taiyuan University of Science and Technology, Shanxi, P.R. China, 030024;

State Key Laboratory for Manufacturing Systems Engineering Xi'an Jiaotong University, Xi'an, P.R. China, 710049;

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正文语种 eng
中图分类人工智能理论;
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Particle Swarm Optimization Using Levy Probability Distribution

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