不可微的 meaning in English
non differentiable
Examples
- The sga ( simplex - genetic algorithm ) , an improved algorithm of genetic algorithm for solving stackelberg - nash equilibrium , is also proposed for the minimax optimization
该算法综合了遗传算法和单纯形法的优点，主要应用于求解目标函数不可微的minimax全局优化。 - Because ga possesses the traits of can global random search , the robustness is strong , been use briefly and broadly , it didn ’ t use path search , and use probability search , didn ’ t care inherence rule of problem itself , can search the global optimum points effectively and rapidly in great vector space of complicated , many peak values , cannot differentiable . so it can offset the shortages of nn study algorithm , can reduce the possibility that the minimum value get into local greatly , the speed of convergence can improve , interpolation time shorten greatly , the quantity of training reduce
因为遗传算法具有全局随机搜索能力,鲁棒性强、使用简单和广泛的特点,它不采用路径搜索,而采用概率搜索,不用关心问题本身的内在规律,能够在复杂的、多峰值的、不可微的大矢量空间中迅速有效地寻找到全局最优解,所以可以弥补神经网络学习算法的不足,使陷入局部最小值的可能性大大减少,使得收敛速度提高,训练量减小。 - And the basis of the multi - objective optimization is single objective optimization and minimax optimization ? in the dissertation , some effective optimization methods are developed for the single objective optimization ? the effective methods are as follows : 2 . 1 hybrid simplex - genetic optimization method 0 one of the main obstacles in applying genetic algorithms ( gas ) to complex problems has been the high computational cost due to their slow convergence rate
三目标鲁棒优化命题的最后解决，离不开单目标优化算法的实现和最小后悔度目标minimax优化等一些基本优化问题的解决。本文在综合前人研究的基础上，创造性的提出了几种有效的优化方法： 3 1混合基因优化算法用于解决可微或不可微的单目标优化命题。