| 基于模糊规则优化的改进模糊遗传算法 |
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| 引用本文： | 戚志东,朱新坚,朱伟兴.基于模糊规则优化的改进模糊遗传算法[J].计算机工程与应用,2003,39(27):18-20,38. |
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| 作者姓名： | 戚志东 朱新坚 朱伟兴 |
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| 作者单位： | 1. 上海交通大学自动化系燃料电池研究所,上海,200030
2. 江苏大学电气信息工程学院,镇江,212013 |
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| 基金项目： | 国家863高技术研究发展项目(编号:2002AA517020) |
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| 摘 要： | 该文针对遗传算法的特点,提出了一种基于模糊规则优化的改进模糊遗传算法及其算法结构,即用模糊控制的方法来调整遗传算法中的交叉概率和变异概率,同时寻找与控制对象相匹配的最佳模糊规则。在数学函数上的仿真结果表明,此种模糊遗传算法不仅加快了解的收敛速度,而且大大提高了解的质量。
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| 关 键 词： | 遗传算法 模糊控制 交叉概率 变异概率 |
| 文章编号： | 1002-8331-(2003)27-0018-03 |
An Improved FGA Based on the Optimization of Fuzzy Rules |
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| Qi Zhidong,Zhu Xinjian,Zhu Weixing.An Improved FGA Based on the Optimization of Fuzzy Rules[J].Computer Engineering and Applications,2003,39(27):18-20,38. |
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| Authors: | Qi Zhidong Zhu Xinjian Zhu Weixing |
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| Affiliation: | Qi Zhidong 1 Zhu Xinjian 1 Zhu Weixing 21 |
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| Abstract: | Based on the characteristics of genetic algorithm,an improved fuzzy genetic algorithm(FGA)and its algorithm structure based on the optimization of fuzzy rules are proposed.Fuzzy control method is used to adjust the genetic algorithm's probabilities of crossover and mutation,while searching for the best fuzzy rules correspond to the control objects.The results of simulation on mathematical functions show that this kind of FGA can improve both the convergent speed and the quality of the solution. |
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| Keywords: | Genetic algorithm Fuzzy control Crossover probability Mutation probability |
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