分析结果表明人口迁移算法依概率收敛到全局最优解。
It is proved that the algorithm converges to the global optimum in probability.
用概率论分析了新提出的求解函数全局优化问题的人口迁移算法的收敛性及动态特性。
The convergence property and dynamic characteristics of the newly proposed population migration algorithm for solving global function optimization problems are analyzed by means of probability.
如何利用人工鱼群算法的群智能特性来克服人口迁移算法中人口流动的随机性带来的问题是本文工作的重点。
How to use the swarm intelligence of AFSA to conquer problems caused by the randomness of population's movement in PMA is the key point of this thesis.
通过引入人口迁移的思想，在保证算法收敛性的同时，使M - PSO算法具有良好的优化速度和优化效果。
By introduction of the ideology of population migration, the M-PSO algorithm keeps the convergence and has good performance such as optimization velocity and optimization results.
通过引入人口迁移的思想，在保证算法收敛性的同时，使M - PSO算法具有良好的优化速度和优化效果。
By introduction of the ideology of population migration, the M-PSO algorithm keeps the convergence and has good performance such as optimization velocity and optimization results.
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