不可微的的英文

• non differentiable

• "微"英文翻译    minute; tiny; light; slight
• "的"英文翻译    4次方是 The fourth power of 2 i ...
• "可微的" 英文翻译 :    derivable; differenzierbar differentiable
• "连续可微的" 英文翻译 :    continuously differentiable
• "右方可微的" 英文翻译 :    right hand differentiable; right side differentiable
• "逐项可微的" 英文翻译 :    termwise differentiable
• "次连续可微的" 英文翻译 :    times continuously differentiable
• "从下面可微的" 英文翻译 :    linksseitig differenzierbar differentiable from below; differentiable from the left
• "不可微分的" 英文翻译 :    non-differentiable
• "n次连续可微的" 英文翻译 :    n times continuously differentiable
• "不可微分函数" 英文翻译 :    non-differential function
• "对一个复变量可微的" 英文翻译 :    komplex differenzierbar differentiable with respect to a complex variable
• "连续不可微函数" 英文翻译 :    continuous nondifferentiable function
• "微的" 英文翻译 :    micro-
• "可微分" 英文翻译 :    differentiable
• "可微图" 英文翻译 :    differentiable atlas; differentiableatlas
• "可微性" 英文翻译 :    derivability; derivative; differenzierbarkeit differentiability
• "卑微的" 英文翻译 :    insignifican; lowdown; menial; pimping; simple
• "测微的" 英文翻译 :    micrometric
• "超微的" 英文翻译 :    ultramicro; ultrastructural
• "极微的" 英文翻译 :    atomical; hair; indivishible; indivisible; infinitesimal; minimal; off-chance; teeny
• "轻微的" 英文翻译 :    cold; feeble; gentle; min minor; nominal; slightly
• "衰微的" 英文翻译 :    decadenteffete; effete
• "缩微的" 英文翻译 :    miniature
• "微微的" 英文翻译 :    slight

• 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。