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evolution algorithms
相关语句
  进化算法
     Solution strategies of multi-objective optimization synthesis mainly have mathematic programming method and multi-objective evolution algorithms.
     求解多目标优化综合问题的方法主要有多目标数学规划法和多目标进化算法,以遗传算法为代表的进化算法是建立在生物进化基础上借鉴自然选择和群体遗传激励的随机搜索算法。
短句来源
     Evolution Algorithms by Simulating Species Forming and Multimodal Function Optimization
     模拟生物种族形成的进化算法与多峰函数优化
短句来源
     The new method needs not prior knowledge about the size and structure of the final solution, and it generalized greatly the application of evolution algorithms in engineering.
     该方法不需要事先确定最终解的结构和大小,大大推广了进化算法在工程实践中的应用。
短句来源
     (5) We designed a type of Rate Compatible LDPC (RC-LDPC) codes with zigzag structure for type II hybrid ARQ system. Additionally, combining Gaussian approximation and differential evolution algorithms, we proposed an algorithm for optimizing the degree distribution pairs of irregular RC-LDPC codes.
     (5)提出了应用于II型H-ARQ系统速率兼容LDPC码的构造方法,并且结合高斯逼近原理及差分进化算法,给出了设计非正则速率兼容LDPC码的分量码度序列的算法。
短句来源
     The solution methods mainly have mathematics programming and the multi-objectives evolution algorithms.
     求解方法主要有数学规划法和多目标进化算法
短句来源
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  演化算法
     The results reveal the parallel essence of evolution algorithms.
     从实验结果来看,达到了并行效果,也揭示了演化算法本质的并行性。
短句来源
     Application of Differential Evolution Algorithms in Optimization of Mechanical Design
     差异演化算法在机械优化设计中的应用
短句来源
     Application of Modified Differential Evolution Algorithms in Optimization of Mechanical Design
     改进差异演化算法在机械优化设计中的应用
短句来源
     Application of Differential Evolution Algorithms in Determining the Charge on an Electron
     差异演化算法在计算基本电荷中的应用
短句来源
     Differential Evolution Algorithms with Extinction Based on Space Contraction
     基于空间收缩的种群灭亡差异演化算法
短句来源
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  “evolution algorithms”译为未确定词的双语例句
     Dynamic Reactive Power Optimization on the Basis of Family Eugenics Based Evolution Algorithms
     基于家族优生学进化算法的电力系统动态无功优化
短句来源
     RECONFIGURATION OF DISTRIBUTION NETWORKS BASED ON FAMILY EUGENICS BASED EVOLUTION ALGORITHMS
     基于家族优生学的配网重构
短句来源
     Synthesis of Planar Five-Bar Path Generating Mechanisms Using Differential Evolution Algorithms
     基于DE优化方法的混合驱动平面五杆机构实现点位对应综合
短句来源
     On the Optimum Synthesis of Six-bar Linkages for Dwell Mechanisms Using Differential Evolution Algorithms
     基于差分进化算法的六杆间歇机构优化综合
短句来源
     Multi-stage portfolio optimization using differentiation evolution algorithms
     基于微分进化算法的多阶段投资组合优化
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  evolution algorithms
We show that the mathematical results on evolution algorithms are consistent with experimental data on genetic evolution.
      
Evolution algorithms that provide stability of populations are not trivial.
      
Differential evolution algorithms using hybrid mutation
      
This study demonstrates that it is now possible to match complex offshore wave-evolution algorithms with linear theory runup solutions for the purpose of obtaining realistic tsunami inundation estimates.
      
This paper presents differential evolution algorithms, which use different adaptive or self-adaptive mechanisms applied to the control parameters.
      
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According to the peculiarity of the production plan model of an enterprise, an environment evolution algorithm or genetic optimization algorithm is proposed. It is a combination of the methods of expert system and linear programming. A part of the parameters of the key constraints in the model is taken as genetic factors. Production plan model for a textile enterprise is used as an example to illustrate how the algorithm is to be realized in practice.

根据企业生产计划模型的特点,提出了一种将专家系统方法和线性规划方法结合于其中,以模型的部分关键约束参数作为遗传囵子的遗传优化算法,即环境进化算法.并以纺织企业生产计划模型为例,介绍了环境进化算法的具体实现.

Genetic algorithm, evolutionary programming and evolution strategies are all based on the idea of natural evolution. Those algorithms are differentiated by the way of getting new generation. But the new one is related with the last generation only. So they are all Markov processes. A unified expression of the state transition matrix was proposed. A lower bound of the converge speed and the convergence of the evolution algorithm were derived. Finally, it was explained why the genetic...

Genetic algorithm, evolutionary programming and evolution strategies are all based on the idea of natural evolution. Those algorithms are differentiated by the way of getting new generation. But the new one is related with the last generation only. So they are all Markov processes. A unified expression of the state transition matrix was proposed. A lower bound of the converge speed and the convergence of the evolution algorithm were derived. Finally, it was explained why the genetic algorithm can get a better solution quickly while it needs a long time to get the global solution.

遗传算法、进化规划和进化策略这三类进化算法都是基于对自然进化的模拟,其区别在于产生下一代群体的规则不同,但下一代群体的产生又都是仅依赖于其父代,因而进化算法的运行过程可以视为一个Markov过程,其状态转移矩阵可以表示成一个统一的形式.利用矩阵范数的基本性质,得到了进化算法收敛速度的一个下界,同时也得到了进化算法收敛性的一个证明,并由此解释了遗传算法能很快地得到一个较好的解而要花费较长时间才能得到最优解的原因,为今后加快进化算法收敛速度指出了一个可行的研究方向

A sort of autonomous agent construction method based on adaptive symbiotic evolutionary model was proposed, and by using adaptive symbiotic evolution algorithm (ASE) as an evolutionary reinforcement learning method, Which can design neural network decision making systems effectively. while at the same time this method can accelerate the learning and convergence speed in the behavior evolution problem of multi agent autonomous system, and it also prevents premature convergence and promotes population...

A sort of autonomous agent construction method based on adaptive symbiotic evolutionary model was proposed, and by using adaptive symbiotic evolution algorithm (ASE) as an evolutionary reinforcement learning method, Which can design neural network decision making systems effectively. while at the same time this method can accelerate the learning and convergence speed in the behavior evolution problem of multi agent autonomous system, and it also prevents premature convergence and promotes population diversity. It uses this model in the study of artificial creature matching criterion, through an efficient living and behavior learning period in the environment, the male and female individuals will all be able to learn a successful matching communication strategy.

文章研究了一类基于自适应共生进化模型的自主体构造方法,提出了基于自适应共生进化算法(ASE)的一种进化强化学习方法,该方法不仅可以高效地进行神经网络决策系统的设计,而且在多自主体组成的自律系统的群体行为进化中可快速学习而收敛,并且通过多样度调节维持了群体多样性,克服了未成熟收敛现象。研究者将该方法用于人工生物中求偶通讯规范的研究,通过在环境中的生存和行为学习,雌雄个体都可有效地学习到成功的求偶通讯规范。

 
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