The GA implementation USES dynamic crossover and mutation probabilistic rate for faster convergence.
其中利用一种动态的交叉率和变异率，有效地加快了收敛的速度。
Several operations such as crossover and mutation are combined so as to improve the convergence rate in the process of parametric estimation.
方法中引入几种交叉和变异算子同时操作，大大提高了辨识效率和辨识精度。
It applies adaptive crossover rate, which is changed with the maximum colony adaptation degree and the average colony adaptation degree of each generation.
该算法的交叉率随种群中的最大适应度值和每代种群的平均适应度值的变化而自动改变；变异率随适应度值和进化代数的变化而自动调节。
It applies adaptive crossover rate, which is changed with the maximum colony adaptation degree and the average colony adaptation degree of each generation.
该算法的交叉率随种群中的最大适应度值和每代种群的平均适应度值的变化而自动改变；变异率随适应度值和进化代数的变化而自动调节。
应用推荐