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Modified constriction particle swarm optimization algorithm

机译:改进的压缩粒子群算法

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摘要

To deal with the demerits of constriction particle swarm optimization (CPSO), such as relapsing into local optima, slow convergence velocity, a modified CPSO algorithm is proposed by improving the velocity update formula of CPSO. The random velocity operator from local optima to global optima is added into the velocity update formula of CPSO to accelerate the convergence speed of the particles to the global optima and reduce the likelihood of being trapped into local optima. Finally the convergence of the algorithm is verified by calculation examples.
机译:针对压缩粒子群优化算法(CPSO)的缺点,如重新陷入局部最优,收敛速度慢等,通过改进CPSO的速度更新公式,提出了一种改进的CPSO算法。从局部最优到全局最优的随机速度算子被添加到CPSO的速度更新公式中,以加快粒子收敛到全局最优的速度,并减少陷入局部最优的可能性。最后通过算例验证了算法的收敛性。

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