algorithm convergence

基本解釋

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遺傳算法的運行機制，并對遺傳算法的收斂性作了詳細分析。
The algorithm is deduced and difference equation of parameter error given by which the algorithm convergence is proved theoretically.
對該算法進行了推導，并給出了參數誤差的差分方程，在理論上證明了算法的收斂性。
For accelerating the algorithm convergence and avoiding the local optimization, an individual learning mechanism is often applied to generic algorithm to improve algorithm performance.
在遺傳算法中引入個體學習機制能夠提高算法的性能，避免算法收斂過慢或陷入局部最優(yōu)。