A Basic Study on Particle Swarm Optimization Based on Chaotic Spike Oscillator Dynamics
A Basic Study on Particle Swarm Optimization Based on Chaotic Spike Oscillator Dynamics
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DOI：
10.1007/978-3-642-34487-9_25
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发表时间：
2012-11
期刊：
影响因子：
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通讯作者：
Yoshikazu Yamanaka;T. Tsubone
中科院分区：
文献类型：
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作者：
Yoshikazu Yamanaka;T. Tsubone
本文提出了一种粒子群优化算法。基于混沌尖峰振荡器动力学的粒子群算法。CSOPSO)。该方法具有不需要随机元素的最优搜索能力。由于基本粒子动力学在由速度和位置组成的相空间上表现为混沌行为，因此粒子在搜索空间上也表现为混沌运动。位置搜索范围所对应的混沌吸引子大小可以用单参数控制。重点研究了吸引子大小对搜索能力的影响。通过对一些基准问题的比较，考虑了该算法的有效性。
In this paper, we propose a particle swarm optimization(abbr. PSO) based on chaotic spike oscillator dynamics(abbr. CSOPSO). Our method has ability to search optima without stochastic elements. Since the basic particle dynamics exhibits chaotic behavior on phase space consisting of the velocity and position, particles on the search space move with chaotic motion. Size of the chaotic attractor corresponding to search range of position can be controlled by single parameter. We focus on influence between size of the attractor and searching ability. The effectivity of CSOPSO by comparing with a previous PSO by some benchmark problems is considered.