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genetic operators
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  遗传算子
     Representation and Genetic Operators in Tasks Matching & Scheduling by Genetic Algorithms
     任务分配与调度中的遗传算法:知识表示与遗传算子研究
短句来源
     Genetic Operators in Task Matching and Scheduling
     任务分配与调度中遗传算子的设计
短句来源
     Analysis on Genetic Operators
     遗传算法中遗传算子的分析
短句来源
     Analysis on the Genetic Operators of Partheno-Genetic Algorithm
     单亲遗传算法的遗传算子分析
短句来源
     Analysis on Genetic Operators
     遗传算子的分析
短句来源
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  遗传操作算子
     The structure of DNA genetic algorithm is provided, and its genetic operators are discussed.
     给出了DNA遗传算法的结构 ,讨论了遗传操作算子
短句来源
     A new DNAEA(encoding methodbased on evolutionary algorithm) is proposed based on the structure and genetic mechanism of biological DNA. The coding structure of DNA chromsome is provided,and its genetic operators are discussed.
     基于生物DNA的结构和遗传机制,提出一种新颖的基于DNA编码方法的进化算法(DNA EA),给出了DNA染色体的编码结构,讨论了遗传操作算子
短句来源
     Secondly, by use the two new genetic operators, construct two new hybrid genetic algorithms called FP _HGA(I)and FP _HGA(II), the flexible polyhedron directional evolution operator and the flexible polyhedron crossover operator are embedded into the FP _HGA(I)and FP _HGA(II)respectively.
     以这两个新的遗传操作算子和柔性多面体搜索算法为基础 ,提出了两种新的混合遗传算法 FP_ HGA( )、FP_ HGA( ) . 在 FP_ HGA( )中 ,嵌入了柔性多面体方向进化算子和柔性多面体搜索算法 ;
短句来源
     One belongs to simple genetic algorithm,which adopts character coding method and uses ordinary genetic operators.
     一种是简单遗传算法,它采用等长度字符代码编码方法,使用常规的遗传操作算子
短句来源
     The algorithm is improved in the following three aspects: the definition of fitness function,the genetic operators and the parameters selection.
     该方法针对无向图多划分的特点,分别对适应度函数、遗传操作算子以及参数选取等方面进行了改进。
短句来源
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  遗传操作
     The structure of DNA genetic algorithm is provided, and its genetic operators are discussed.
     给出了DNA遗传算法的结构 ,讨论了遗传操作算子。
短句来源
     A new DNAEA(encoding methodbased on evolutionary algorithm) is proposed based on the structure and genetic mechanism of biological DNA. The coding structure of DNA chromsome is provided,and its genetic operators are discussed.
     基于生物DNA的结构和遗传机制,提出一种新颖的基于DNA编码方法的进化算法(DNA EA),给出了DNA染色体的编码结构,讨论了遗传操作算子。
短句来源
     Secondly, by use the two new genetic operators, construct two new hybrid genetic algorithms called FP _HGA(I)and FP _HGA(II), the flexible polyhedron directional evolution operator and the flexible polyhedron crossover operator are embedded into the FP _HGA(I)and FP _HGA(II)respectively.
     以这两个新的遗传操作算子和柔性多面体搜索算法为基础 ,提出了两种新的混合遗传算法 FP_ HGA( )、FP_ HGA( ) . 在 FP_ HGA( )中 ,嵌入了柔性多面体方向进化算子和柔性多面体搜索算法 ;
短句来源
     One belongs to simple genetic algorithm,which adopts character coding method and uses ordinary genetic operators.
     一种是简单遗传算法,它采用等长度字符代码编码方法,使用常规的遗传操作算子。
短句来源
     The algorithm is improved in the following three aspects: the definition of fitness function,the genetic operators and the parameters selection.
     该方法针对无向图多划分的特点,分别对适应度函数、遗传操作算子以及参数选取等方面进行了改进。
短句来源
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  “genetic operators”译为未确定词的双语例句
     Analysis of Genetic Operators
     遗传算法中常用算子的分析
短句来源
     For the implementation of self learning in fuzzy logic control this paper proposes genetic algorithm to optimize the fuzzy set partitions. The improved encode method and genetic operators are given and the simulation for temperature control system using this method is studied. The results show the proposed method is valid.
     为了使模糊控制器具有自学习能力,本文将遗传算法与模糊控制相结合,提出了使用遗传算法对模糊子集进行划分的优化方法,并根据模糊控制的特点,给出了改进的编码方法和交叉算子,加快了算法的收敛速度.应用该方法对锅炉过热汽温进行了仿真研究,结果表明本文提出的基于遗传算法的模糊控制优化方法是很有效的.
短句来源
     Based on the character of Portfolio choice model, this article studies coding, genetic operators and operators' parameter and designs a genetic algorithm which can solve portfolio model.
     针对投资组合模型的特点,研究了遗传算法的编码、算子和算子参数,设计出了一个能够求解投资组合模型的遗传算法.
短句来源
     Moreover, genetic operators were selected by adaptive algorithm to avoid unwanted early convergence.
     为避免网络的过早收敛,对传统的遗传BP网络进行了改进,应用自适应算法选择遗传算子值。
短句来源
     By using the fitness function and the genetic operators,(R-GA) can get a global convergence solution rapidly.
     通过适度函数和遗传因子,R-GA可以快速地实现全局收敛。
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  genetic operators
These methods maintain populations of individuals with nonlinear chromosomal structure and use 'genetic' operators enhanced by the problem specific knowledge.
      
Furthermore, the function of several genetic operators and the effect of the parameters of genetic optimization on the efficiency of the solution has been numerically examined.
      
The heuristic rules based on the concept of fully stressed design are introduced through special genetic operators, which use the information concerning the stress distribution of structural members.
      
The proposed GA uses not only conventional genetic operators, but also a new heuristic "hypermutation" operator suggested in this work.
      
The purpose of the unexpressed part is to preserve information susceptible to be lost by the application of genetic operators, and thus to maintain the diversity of the search.
      
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The authors make use of the recently revived genetic algorithm(GA)method to design LQ (LinearQuadratic)regulator so as to improve greatly its ability to solve Riccati equation in the problem ofautomatic rendevous and docking(RVD)system.GA reduces greatly computation, and guarantees rapal and ace convergenceIn the GA dcsigD of regulator for RVD.the quadratic performance index is rcgnrded as the fitnessfunction and the feedback gain matrix is obtained mathematically by utiliaing three genetic operators:sckction(reproduction),crossover(mating),and...

The authors make use of the recently revived genetic algorithm(GA)method to design LQ (LinearQuadratic)regulator so as to improve greatly its ability to solve Riccati equation in the problem ofautomatic rendevous and docking(RVD)system.GA reduces greatly computation, and guarantees rapal and ace convergenceIn the GA dcsigD of regulator for RVD.the quadratic performance index is rcgnrded as the fitnessfunction and the feedback gain matrix is obtained mathematically by utiliaing three genetic operators:sckction(reproduction),crossover(mating),and mutation. Simulation resultS allow that,for solvingXieeati equation, GA method bas four advantages,namely.I)Fast convergence.GA,which is called implicit parallelism,searches from a population ofPOints, not just a single point. From Fig.2 the results converge after only 40 generations.2)TrUe global optimum, not local optimum. GA uses probabilistic transition rules,notdeterministic transition rules3) Simplicity in computation. Each gain in the gain matrix is represented by a 8-bit string.Thestrings are concatenated to produce 64-bit string,each string representing one feedback design.GAworks with these codings(strings),not the feedback gains themselves4) Wide applicability.GA considers the quatratic performance index as the fitness function.GA"scsit,Instead of derivative or other information,to evaluate potential solutions.GA can operate'blind.

本文提出应用遗传算法求解黎卡及方程,并将这一方法用于设计自动交会控制器.遗传算法是一种基于自然选择和群体遗传学机理的参数搜索方法,它将达尔文的适者生存策略与人工染色体中的随机而结构化的信息交换相结合,既消除了求解过程的不适应因素,又利用了解中已有的知识,从而大大加快了优化速度和能力,且计算比直接解黎卡提方程要简单.航天器自动交会控制系统的仿真结果表明,这一方法是有效的.

This paper presents sonte modificationsof the Genetic Algorithms (GAs) for improving systemperformance in applying to electric power economic dis-paich. Ihe purpose of the paper is trying to find thebest operaiing point for Genetic Algorithms io workwith. Two leveis of problems have been dealt with forperformance imprcoement: first i's choosing a suitablegenetic strategy, second is tuning various parametervalues for setected genetic strategies. Both lcoels havebeen tested on a 6 generators unit. The test results...

This paper presents sonte modificationsof the Genetic Algorithms (GAs) for improving systemperformance in applying to electric power economic dis-paich. Ihe purpose of the paper is trying to find thebest operaiing point for Genetic Algorithms io workwith. Two leveis of problems have been dealt with forperformance imprcoement: first i's choosing a suitablegenetic strategy, second is tuning various parametervalues for setected genetic strategies. Both lcoels havebeen tested on a 6 generators unit. The test results arecompared regarding to on-line and off-line system per-formances. The overall study clearly shows that thesystem performance could be greatly enhanced with ad-vanced genetic operators and optimal choice of parame-ter values.

本文介绍了在电力经济调度中用于改善系统运行性能的遗传算法的某些修改。目的是试图找出供遗传算法使用的最佳运行点。为了改善运行性能,涉及到问题的两个阶段:即首先是选择一种适当的遗传策略,其次是为所选定的遗传策略对各种参数的值进行协调。这两个阶段均已在六机系统中经过试验,并按照在线及离线两种情况对试验结果进行了比较。全部研究工作清楚地表明,采用先进的遗传算子及优化选择参数值能使系统性能显著增强。

A flew approach based on genetic algorithm for 0-1 programming with linear constraints is proposed. It avoids some troubles caused by classical genetic algorithm. Some new genetic operators are used.

本文提出一种基于遗传算法的求解带线性约束0—1规划问题的新途径,避免了传统遗传算法处理约束时所产生的问题.同时,由于采用与传统遗传算法完全不同的编码方式,对遗传算子的计算方法也进行了修改,并给出了几个算例。

 
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