| 1. | Parameter of parallel multi - deme fuzzy genetic algorithm
并行多种群模糊遗传算法参数 |
| 2. | Self - learning hybrid fuzzy adaptive genetic algorithm
基于特殊二进制编码的自学习模糊遗传算法 |
| 3. | Solving unit commitment problem based on fuzzy genetic algorithm
基于模糊遗传算法的机组组合问题的求解 |
| 4. | Fuzzy genetic algorithm - based electro - hydraulic servo system control
基于模糊遗传算法的电液位置伺服系统控制 |
| 5. | Parameter optimization in industrial process control based on fuzzy genetic algorithm
基于模糊遗传算法的工业过程控制参数优化研究 |
| 6. | They learn from others " strong points to offset one ' s weakness , therefore two research direction - genetic fuzzy system and fuzzy genetic algorithm ( fga ) - appear
现阶段，模糊遗传算法的发展还不十分成熟，对其认识也众说纷纭。 |
| 7. | On the one hand , ga can be used to process the fuzzy information in the imprecise circumstance . on the other hand , fuzzy logic is regard as tool to solve some problems concerning ga
一方面用遗传算法处理非精确环境下的模糊信息，另一方面用基于模糊逻辑的疗法来处理现有遗传算法中的问题，相互取长补短，由此发展了两个方向? ?遗传模糊系统与模糊遗传算法。 |
| 8. | The running result of practical example applied in this paper show that the genetic algorithm is a kind of excellent algorithm because its running course is very simple and the optimal result is enough and it can be applied in many domains
本文中所采用的实例的运行结果更说明了交互式模糊遗传算法的整个运行过程简单且计算有效，是一类优秀的通用性强的重构算法。 |
| 9. | Majority think that fga is the ga resulting from the integration that the use of fuzzy tools and fuzzy logio - based techniques for modeling different ga components and adapting ga control parameters , with the goal of improving performance
大部分学者认为模糊遗传算法是用基于模糊逻辑的模糊工具或模糊逻辑技术来优化遗传算法的组成成分或控制参数，来提高算法性能。 |
| 10. | The results of optimization on mathematical functions showed that the shortcoming of sga can be overcome , and the relying on the initialization of parameters can be effectively avoided . the quality of the solution and the convergent speed also can be improved
函数优化算例表明,模糊遗传算法( fga )能有效地消除遗传算法对参数初值的依赖性,提高寻优质量,改善收敛性。 |
