适应值

shì yìnɡ zhí
  • adaptive value
适应值适应值
  1. 有限的智力是否有适应值呢?

    Is there an adaptive value to9 intelligence ?

  2. 有限的智力是否有适应值呢?这也是此项研究的课题。

    Is there an adaptive value to9 intelligence ? That 's the question behind this new research .

  3. 内层GA得到的最佳染色体适应值用来评价外层GA相应染色体。

    The fitness value of the optimal chromosome from interna-lays GA is used to evaluate corresponding chromosomes of external-layer GA.

  4. 我们给出了DNA计算中序列设计的支持系统:计算由多个评价指标的线性和组成的适应值函数的最小值。

    We develop support system for sequence design in DNA computing , which minimizes the evaluation function calculated as the linear sum of the plural evaluation terms .

  5. 选择疫苗时,将接种了疫苗的个体的适应值小于父代适应值的个体,按一定的概率接受该个体,克服了GA欺骗问题。

    The individuals below fitness value of its parents are accepted in a probability , overcoming the trick problem in GA.

  6. 为了解决多目标进化算法中适应值指派(fitnessassignment)的耗时问题,提出了一种新颖的适应值指派方法&占优树。

    To solve the time-consuming problem of the fitness assignment in the multi-objective evolutionary algorithm , this paper proposes a novel fitness assignment & dominating tree .

  7. 以GA运行过程中输出的适应值序列为研究对象,通过功率谱和重标定域两种方法发现GA的输出序列存在自相似行为。

    By introducing the power spectrum density analysis and re-scaled range method , the self-similar behavior is revealed in GA ′ s fitness series .

  8. 同时,计算各个制造资源组合的适应值,利用MATLAB作出适应值趋势图。

    At the same time , the program calculates the value for every combination of manufacturing resources . By MATLAB , it describes a trend picture with these values .

  9. 基于适应值共享GA及MPGA的多路径规划研究

    Research of Multi-path Planning Based on Fitness Sharing GA & MPGA

  10. 选择算子中有依适应值比例选择,Boltzmann选择,排序选择,联赛选择,精英选择等算子。

    The selection operator includes the fitness proportion selection , Boltzmann selection , ranking selection , tournament selection and elitist selection operator .

  11. 多目标演化算法的研究热点集中在Pareto最优概念的种群个体的比较与排序、适应值赋值与小生境技术等方面。

    The researches on multi-objective evolutionary algorithms focus mainly on the Pareto-based comparison and ordering of individuals , fitness assignment and niche techniques , etc.

  12. 该方法对历史数据进行离散化后,以NB分类的错误率作为粒子适应值函数,构建软件缺陷预测模型。

    After discretizing the original data , the error rate of NB is taken as fitness function of the particle , and a software defect prediction model is constructed .

  13. SAGS算法利用种群关键特征的变化趋势,设计了可变的适应值函数、交叉概率函数和变异概率函数。

    Using variational trend of key characteristics of population , SAGS algorithm constructed flexible fitness function , cross probability function and mutative probability function .

  14. 用Pareto排序得到的rank值和拥挤距离共同反映的个体的适应值来决定个体间的差异程度,用相似性描述个体间的类似程度,从而实现了对种群的分级。

    Reflecting individuals ' difference degree with individual 's fitness which is together determined by the rank value and the crowded distance , describing individuals ' similar degree with similarity , so realizes population classification .

  15. 本文定义和使用稀松密度来保持群体中个体的均匀分布,并将个体的Pareto强度值和稀松密度合并到个体的适应值定义中。

    The paper define and use loosing density to maintain a good spread of solution in the population , and define the fitness of the individual through Pareto strength and crowding density .

  16. 该优化策略将模拟移动床的最大吸附剂生产率作为优化问题的目标函数,采用模拟移动床的TMB模型来计算微粒群优化算法的适应值。

    The optimization algorithm ′ s objective function is the adsorbent productivity and the particle swarm optimization ′ s fitness is calculated with TMB model .

  17. 本文提出了具有适应值曲面结构自学习能力的多区域并行局部搜索算子PLS和受控交叉算子GC,定性地分析了它们的作用机制。

    This paper proposed a kind of parallel local search operator PLS and a guided crossover operator GC that have self-learning ability of the structure of fitness landscape . The operation mechanisms of the two proposed operators were qualitatively analyzed .

  18. 该算法定义和使用稀松密度来保持群体中个体的均匀分布,并将个体的Pareto强度和稀松密度合并到个体的适应值定义中,使得搜索向Pareto最优解集的方向进行并防止早熟;

    To maintain a good spread of solution in the population , the Loosing - density is defined and used in this algorithm , the fitness of the individual through Pareto strength and Loosing - density is also defined .

  19. 本文用遗传算法优化工程中广泛使用的PID控制器的参数,采用变参数区间、变交叉变异概率等方法提高计算速度,并对适应值函数进行了改进。

    This dissertation uses Genetic Algorithm to choose optimum parameters for the widely used PID controllers . In the optimization calculation process , mutation rate , cross rate and parameter range are adaptively changed to accelerate optimization process . The fitness function is also changed according to different requirements .

  20. APSO算法是在PSO算法基础上,根据各参数与粒子群适应值的关系,引入启发式规则,使各参数随求解问题的不同在寻优过程中自适应地变化,以便获得最优解。

    According to the relationship between the control parameters and the fitness value of particles , APSO adjusts parameters adaptively in optimization process to find the global optimum based on some heuristic rules .

  21. 此算法根据Pareto占优关系评价个体适应值,采用模拟退火进行局部搜索,并结合交叉算子和基于网格密度的选择机制改善算法的收敛速度和解的均衡分布。

    The method evaluates the individual fitness based on Pareto dominance relationship , applies simulated annealing to local search , and uses the crossover operator and a grid-density-based selection scheme to improve the convergence of the algorithm and to enhance the uniform distribution of solutions .

  22. 基于混沌遗传算法(HGA)的函数优化,将混沌优化方法嵌入到GA中替代GA变异算子,以改善变异个体适应值,加快了算法收敛。

    The function based on hereditary algorithm ( HGA ) of the Chaos is optimized , optimization the method of the Chaos is imbedded in the operator of GA to substitutes mutation , in order to improving the suiting value of individual , and accelerating algorithms .

  23. 利用KKT条件求出的功率分配结果和子载波分配方案可以得到系统的传输速率,将该传输速率作为子载波分配方案的适应值。

    The transfer rate of the system can be gotten through the power allocation result obtained by KKT conditions and the subcarrier allocation program . The transfer rate of the system is regarded as the fitness of the individual .

  24. 自适应调整峰半径的适应值共享遗传算法

    The fitness sharing genetic algorithm with self-adaptive control of peaks radii

  25. 用适应值激励机制提高遗传算法的效率

    Improving the Efficiency of Genetic Algorithms by Using Fitness Stimulating Mechanism

  26. 针对3种不同的适应值度量方案,进行仿真研究。

    A simulation study is performed for three adaptation measurement concepts .

  27. 适应值共享对遗传算法选择概率的影响分析

    Influence of fitness sharing on the selection probability of genetic algorithm

  28. 最后通过适应值函数评价染色体。

    In the end , evaluate the chromosome by fitness function .

  29. 最优多用户检测问题适应值曲面分析

    Analysis of the fitness landscape of optimum multiuser detection problem

  30. 引入适应值曲面结构的小生境遗传算法初探

    A Class of Niche Genetic Algorithms by Exploring Structure of Fitness Landscape