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   crossover 在 计算机软件及计算机应用 分类中 的翻译结果: 查询用时:0.138秒
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crossover
相关语句
  交叉
    CALCULATING FORMULA AND GRAPHIC METHOD OF GEOMETRIC PARAMETERS BETWEEN TWO CROSSOVER LINES
    交叉两直线间几何参数的计算公式及图解方法
短句来源
    Efficiency Analysis of Crossover Operationin Real-coded Genetic Algorithm
    实数编码遗传算法中交叉操作的效率分析
短句来源
    The Genetic Algorithm with Crossover Operator Employing Lattice Methods
    用网格实现交叉操作的遗传算法
短句来源
    Influence of Crossover Operators on the Diversity in Genetic Algorithms
    遗传算法中交叉算子对群体多样性的影响
短句来源
    Limit Consistency of Crossover Operator
    交叉算子的极限一致性
短句来源
更多       
  交叉
    CALCULATING FORMULA AND GRAPHIC METHOD OF GEOMETRIC PARAMETERS BETWEEN TWO CROSSOVER LINES
    交叉两直线间几何参数的计算公式及图解方法
短句来源
    Efficiency Analysis of Crossover Operationin Real-coded Genetic Algorithm
    实数编码遗传算法中交叉操作的效率分析
短句来源
    The Genetic Algorithm with Crossover Operator Employing Lattice Methods
    用网格实现交叉操作的遗传算法
短句来源
    Influence of Crossover Operators on the Diversity in Genetic Algorithms
    遗传算法中交叉算子对群体多样性的影响
短句来源
    Limit Consistency of Crossover Operator
    交叉算子的极限一致性
短句来源
更多       
  “crossover”译为未确定词的双语例句
    The Traversing of Crossover in Genetic Algorithms
    遗传算法交换操作的遍历性
短句来源
    Genetic Algorithm with Multiple Individuals Crossover
    多个体参与交叉的遗传算法
短句来源
    The Accessibility of Crossover in Genetic Algorithms
    遗传算法交换操作的可达性
短句来源
    Pareto Multiobjective Genetic Algorithm with Multiple Chromosomes Crossover
    多个体参与交叉的Pareto多目标遗传算法
短句来源
    A Dynamical Evolutionary Algorithm with Multiple-chromosomes Crossover
    多个粒子参与交叉的一种动态演化算法
短句来源
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  crossover
At each iterate, by reduplication, crossover and mutation, a finite set of points can be used.
      
For the genetics algorithm, chromosome coding, fitness function, parameters selection, and the basic genetics operation including selection, crossover and aberrance, are described.
      
Eight young, healthy male volunteers were exposed to two 24 h periods of continuous wakefulness during the crossover experiment.
      
Numerical investigation of aerodynamic performance influenced by circumferentially pre-swirling coming flow on the crossover and
      
Numerical investigation is implemented on aerodynamic performance inside the crossover and de-swirling cascade of a multistage centrifugal compressor.
      
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As general stochastic search algorithms, geneitc algorithms (GA's) have been applied to a variety of research fields such as function optimization, machine learning, etc.. Classical GA's can not surmount the ordering problems well. In this paper, for a kind of classical ordering problems——the traveling salesman problem, we first illustrate the necessity of using normalization techniques to calculate appropriate evaluation functions and then design a new heuristic crossover operator which is more effective...

As general stochastic search algorithms, geneitc algorithms (GA's) have been applied to a variety of research fields such as function optimization, machine learning, etc.. Classical GA's can not surmount the ordering problems well. In this paper, for a kind of classical ordering problems——the traveling salesman problem, we first illustrate the necessity of using normalization techniques to calculate appropriate evaluation functions and then design a new heuristic crossover operator which is more effective than similar operators published before.

遗传算法作为一种通用随机搜索算法,在函数优化、机器学习等许多方面获得了很好的结果.但是,常规的遗传操作对于有序问题效果不理想.本文分析了一种典型的有序问题——旅行售货员问题,根据其特点并结合遗传算法的模式理论,设计出一个新的启发式遗传交换操作.理论分析和实验结果显示这种交换操作的效果大大好于较通用的有序交换操作,也优于Grefenstette的贪心方法.

According to the theory of higher geometry and engineering graphics, the calculating formula of geometric parameters between two crossover lines is set up and its graphic method is given. This is of important significance for mine design, conduit assemble, structural member and computer aided design

本文应用高等几何及工程图学的有关知识,建立了交叉两直线产几何参数的计算公式,并给出了图解方法。对矿井设计、管道安装、建筑构件及计算机辅助设计都有着重要的意义。

genetic algorithm is used to make near-optimal cluster for parts in group technology, based on p-median model. In order to satisfy complex constraints of P-median, the sequential code (0 or 1 ) is taken to symbolize chromosomes which are divided into two parts and crossover and mutation are independently made. Results indicate that: when minimal sum of within cluster distance is taken to be performance criterion, the above method is superior to K-means algorithm.

采用遗传算法对成组技术中的零件进行近优分蔟,提出了用0、1码分段构造染色体和分段交叉、变异的策略来满足P-中位模型复杂约束的要求。实验结果表明,当以类内样本距离之和作为评价准则时,该算法明显好于K-平均算法。

 
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