algorithm convergence

基本解释

This paper particularly analyzed the work mechanism and the algorithm convergence of the niching genetic algorithms.
文章扼要分析了小生境遗传算法的运行机制，并对遗传算法的收敛性作了详细分析。
The algorithm is deduced and difference equation of parameter error given by which the algorithm convergence is proved theoretically.
对该算法进行了推导，并给出了参数误差的差分方程，在理论上证明了算法的收敛性。
For accelerating the algorithm convergence and avoiding the local optimization, an individual learning mechanism is often applied to generic algorithm to improve algorithm performance.
在遗传算法中引入个体学习机制能够提高算法的性能，避免算法收敛过慢或陷入局部最优。