1) population size
种群规模
1.
Focusing on the problems existing in some genetic algorithms that population size is difficult to estimate or compute,a genetic algorithm with varying population size based on generational gap information(SAVPGA) is proposed.
针对遗传算法种群规模难以估计的问题,提出了一种基于代沟信息的可变种群规模遗传算法。
2.
In the view of the population size and individuals space, the factors that affect the performance of genetic operator were analyzed.
从种群规模和个体空间的角度分析了影响遗传算子性能的因素,在遗传算法(GA)的基础上设计了一种搜索区域可变、群体规模可变的最优家族遗传算法(OFGA)。
3.
Secondly,an adaptive adjustment method of the population size is given based on the search areas measure and the search granularity.
首先,依据各种群最优个体的分布给出搜索区域动态变化的条件和策略;其次,基于搜索区域的测度和搜索粒度给出种群规模自适应调整方法;再次,从搜索区域的测度和种群规模等角度定量分析算法的性能;最后,通过两个典型函数优化验证算法的有效性。
2) varying population size
变种群规模
3) self-adaptive population dimension
种群规模自适应
1.
The legitimacy of self-adaptive population dimension genetic operatings of selection, crossover and mutation is analyzed ,and suggested equation of crossover rate is givern.
本文分析了种群规模自适应遗传算法在选择、交叉、变异操作中的合法性 ,给出了交叉率的建议公式。
4) cluster law
种群规律
1.
The paper brings forth the cluster law of science & technology development based on knowledge metrics.
在知识计量学的思想基础上提出科技发展种群规律的动力模型,从模型中推导出普赖斯指数增长规律。
5) population size dependent contact rate
种群规模制约接触率
6) genetic algorithm with varying population size
变种群规模遗传算法
补充资料：种群增长率(见种群出生率)
种群增长率(见种群出生率)
种群增长率见种群出生率。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条