| 1. | Selection of mutation probability of floating - point number code genetic algorithm
浮点数编码遗传算法变异概率的选取 |
| 2. | According to the distinguished result , the algorithm adaptively sets the mutation rate
根据辨识结果，自适应地设置变异概率。 |
| 3. | The coding and decoding methods , key parameters and the definition of fitness function are discussed
通过实验，对交叉概率、变异概率的确定方法进行了讨论。 |
| 4. | ( a ) chaos initialization is adopted and subpopulations are classified as several types according to the values of crossover and mutation probability
利用混沌思想产生初始群体，并依交叉和变异概率值对子群体进行分类； b |
| 5. | This paper proposes the array chain chromosome coding and the adaptive ga ( aga ) that combines the self - adaptive mutation probability and simulation anneal punishment function
提出了数组链染色体编码方式，以及基于自适应性变异概率和模拟退火惩罚函数法的适应性遗传算法( aga ) 。 |
| 6. | This dissertation defines two parameters based on the diversity measure as the input of the flc which is used to control the ga ' s crossover probability and mutation probability
本文从群体多样性的角度出发，定义了两个参数作为模糊逻辑控制器的输入变量，输出为遗传算法的交叉概率和变异概率。 |
| 7. | The simulation results indicate the validities of the proposed hybrid optimization algorithm and the compute method of self - adaptive crossover probability and mutation probability . 2
仿真研究表明所提混合优化算法及自适应交叉概率和变异概率的计算方法在求解本文交通信号动态优化控制问题中的有效性。 |
| 8. | In this genetic algorithm , each member in a supply chain alliance has a self - adaptive ability to changes in environment in the genetic process through designing crossover probability and mutation probability
该算法设计了自适应交叉概率和变异概率，使每个个体在遗传过程中对环境变化具有自适应调节能力。 |
| 9. | Besides , proposing an adaptive variation factor to keep the diversity of population , and a novel crossover rule to widen the distribution space of children generations also effectively modified the sga
提出的相应技术包括：采集种群多样性指标用以调整变异概率；改进交叉算子，避免子代收缩，并提高其适应度；新增powell寻优算子，加速局部搜索。 |
| 10. | The difference between this algorithm and traditional genetic algorithm lied in the fact that this algorithm adopted order crossover and cell exchange mutation methods ; at the same time crossover probability and mutation probability were optimized
与传统遗传算法不同的是，该算法采用了顺序交叉和单元交换变异方式，同时对交叉概率和变异概率进行了优化设计。 |
