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uniform mutation
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  均匀变异
     By means of improved evolution strategies (μ+λ+κ)-ES in which decreasing strategy parameter and single-gene Gauss mutation and uniform mutation operators are used, the parameter for optimal control of the robot is found out.
     借助于一种基于单基因Gauss变异和均匀变异相结合、递减型策略参数的改进进化策略(μ+λ+κ)-ES,求出了实现最优控制的参数.
短句来源
     Finally,a new ES,called(μ+λ+k)-ES,is established which is characterized with single-gene Gaussian plus uniform mutation,elitist-reproduction,descending strategy parameter and small population size. Simulation results on a set of 100-dimensional typical test functions are presented.
     最后,建立了单基因Gauss变异与均匀变异相结合、使用精英繁殖、递减型策略参数、小种群规模的(μ+λ+k)-ES,给出了一组100维典型测试函数的仿真计算结果.
短句来源
     In order to break the limit to optimization design of lateral force balance from bit structures,a new optimization design method by genetic algorithm was developed,which employed algorithms of proportional selection,single point crossover,uniform mutation and generation communication.
     为了突破PDC钻头结构对侧向力平衡优化设计的限制,采用比率选择、单点交叉、均匀变异和代沟操作等多项技术,利用遗传算法建立了PDC钻头侧向力平衡优化设计方法。
短句来源
     The genetic algorithms in this thesis adopt the commonly used proportional model, arithmetic crossover operation, and uniform mutation operation.
     本论文采用浮点数编码方法,采用基本遗传算法的算子:比例选择算子、算术交叉算子和均匀变异算子,初步确定了遗传算法运行参数。
短句来源
     The improved GA uses decimal-strings encode, normalized geometric ranking selection, hybrid crossover and uniform mutation.
     改进的遗传算法采用十进制编码,规范化几何秩选择,混合交叉及均匀变异
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  一致变异
     The Effect on Structural Genetic Design of Binary Coding Floating Coding and No Uniform Mutation
     二进制码实数码及非一致变异对结构遗传设计的影响
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  “uniform mutation”译为未确定词的双语例句
     The result indicates that the hybrid algorithms based on rank-based selection, arithmetic crossover and uniform mutation is more effective.
     算例表明,基于排序选择法、算术交叉、均匀变异的遗传模拟退火混合算法较为有效。
短句来源
     On the basis of working principle of generic algorithms,this paper brings forward the methods of encoding binary strings for negotiation issues,defining fitness function based on Nash barging solution,creating initial group,elitist model,recombination operation,uniform mutation,and conforms the span of parameters in generic algorithms and finishing rules of generic algorithms operation.
     提出在遗传算法基础上,针对遗传算法的具体步骤,提出了针对谈判冲突问题的二进制编码方法,基于Nash谈判解的适用度函数的确定方法,初始群体生成的方法,最优个体的保存方法,重组操作方法,变异方法,确定了遗传算法中参数的取值域及终止规则.
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  uniform mutation
Plagiarism is shown to be theoretically superior to uniform mutation for generalised counting-ones problems, and also to outperform uniform mutation on certain classes of random fitness landscapes.
      
In the first case, the probability of maximal success in n iterations is derived in closed form, under uniform mutation.
      
We analyzed the relationship between Ks and GC content under (1) uniform mutation bias, (2) a regional mutation bias, and (3) mutation bias and selection.
      
This paper analyzes the convergence of metaheuristics used for multiobjective optimization problems in which the transition probabilities use a uniform mutation rule.
      
A simple genetic algorithm with roulette wheel selection, elitist model, one point crossover and uniform mutation is used to minimize the weighted global criterion measure.
      
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The effect on truss structural optimization of binary coding、 float coding and nonuniform mutation is discussed. Best fitness and convergence rate of normal float coding are better than that of binary coding for solving minimum weight of truss structural problem. However, the average fitness is bad and approximately equal. In order to overcome this shortcoming, we adopt the no uniform mutation operator. The result shows that the best fitness and average fitness of no uniform mutation are...

The effect on truss structural optimization of binary coding、 float coding and nonuniform mutation is discussed. Best fitness and convergence rate of normal float coding are better than that of binary coding for solving minimum weight of truss structural problem. However, the average fitness is bad and approximately equal. In order to overcome this shortcoming, we adopt the no uniform mutation operator. The result shows that the best fitness and average fitness of no uniform mutation are improved. It also shows that the float coding is effective and convenient for truss structural design.

讨论了在遗传设计中,二进制码、实数码及非一致变异策略对桁架结构优化的影响。指出普通实数码在求解重量最轻的最优桁架结构时,最佳适应度与收敛速度比二进制码优越,但平均适应度相差不大。采用非一致变异策略后,最佳适应度与平均适应度比普通实数码和二进制码都要好。说明了对于带约束的桁架结构优化采用非一致变异策略实数编码方法更加有效、方便。

Turbine cascade optimum design, the typical non-convex optimal problem, has long been a design challenge in the engineering fields. The new type hybrid Genetic Algorithms-whole annealing GeneticAlgorithms have been developed in this paper. Simulated annealing selection and non-uniform mutation are adopted in the whole annealing Genetic Algorithms. Whole annealing Genetic Algorithmsoptimal performance have been tested through mathematical test functions. On this basis, turbinecascade inverse design using...

Turbine cascade optimum design, the typical non-convex optimal problem, has long been a design challenge in the engineering fields. The new type hybrid Genetic Algorithms-whole annealing GeneticAlgorithms have been developed in this paper. Simulated annealing selection and non-uniform mutation are adopted in the whole annealing Genetic Algorithms. Whole annealing Genetic Algorithmsoptimal performance have been tested through mathematical test functions. On this basis, turbinecascade inverse design using whole annealing Genetic Algorithms have been presented. The B-Splinefunction is applied to represent the cascade shape. C-type grid and Godunov scheme are adopted toanalysis the cascade aerodynamic performance. The optimal problem aims to obtain an cascade shapefrom different initial cascade through the given target pressure distribution. The optimum cascadeshape is in well agreement with the target cascade shape. The numerical results show that the wholeannealing Genetic Algorithms are the powerful optimum tools for turbine optimum design or othercomplex engineering design problems.

INTRODUCTIONInthelastfewyearstherehajsbeenagrowinginterestinthenumericalsolutionofconstrainedoptimizationproblemsofturbinegovernedbytheEulerorNavier-Stokesequations.Developmelltofturbinecascadeswithoptimumaerodynamicefficiencyhaslongbeenadesignchalle...

A real_coded genetic algorithm is proposed to solve the form evaluation of planes.According to the mathematical definition of dimensional and tolerancing principles,a mathematical model of flatness evaluation in accordance with the minimum zone condition is presented and the fitness function of genetic algorithm is given.Then the implementation steps of the algorithm are dwelt on. Based on the real_coded method,the genetic operation is composed of roulette wheel selection,real_valued simple crossover and uniform...

A real_coded genetic algorithm is proposed to solve the form evaluation of planes.According to the mathematical definition of dimensional and tolerancing principles,a mathematical model of flatness evaluation in accordance with the minimum zone condition is presented and the fitness function of genetic algorithm is given.Then the implementation steps of the algorithm are dwelt on. Based on the real_coded method,the genetic operation is composed of roulette wheel selection,real_valued simple crossover and uniform mutation.Finally the data in literature are verified by the proposed approach.The results show that the algorithm is superior to others in terms of efficiency and quality of solution in the field of dimension and tolerance evaluation.

将基于实数编码的遗传算法应用于平面度的评定。根据尺寸和公差的数学定义 ,建立完全符合最小区域条件的平面度评定的数学模型 ,并在此基础上给出遗传算法的适应度函数。随后详细地介绍了算法的实现步骤 ,在基于实数编码的基础上 ,遗传选择操作采用一种正比选择策略———转轮法 ,遗传交叉操作采用简单算术交叉法 ,而遗传变异操作是随机均匀实数变异操作。最后对文献 [5 ]的实验数据进行了评定 ,仿真结果表明该算法不仅合理 ,而且效率高、精度高 ,优于其它算法。

 
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