• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>Evolutionary Computation, 2004. CEC2004. Congress on >Adaptive probabilities of crossover and mutation in genetic algorithms based on clustering technique
【24h】

Adaptive probabilities of crossover and mutation in genetic algorithms based on clustering technique

机译：基于聚类技术的遗传算法中交叉变异的自适应概率

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Research on adjusting the probabilities of crossover p/sub x/ and mutation p/sub m/ in genetic algorithms (GA's) is one of the most significant and promising areas of investigation in evolutionary computation, since p/sub x/ and p/sub m/ greatly determine whether the algorithm will find a near-optimum solution or whether it will find a solution efficiently. Instead of having fixed p/sub x/ and p/sub m/, This work presents the use of fuzzy logic to adaptively tune p/sub x/ and p/sub m/ for optimization of power electronic circuits throughout the process. By applying the K-means algorithm, distribution of the population in the search space is clustered in each training generation. Inferences of p/sub x/ and p/sub m/ are performed by a fuzzy-based system that fuzzifies the relative sizes of the clusters containing the best and worst chromosomes. The proposed adaptation method is applied to optimize a buck regulator that requires satisfying some static and dynamic requirements. The optimized circuit component values, the regulator's performance, and the convergence rate in the training are favorably compared with the GA's using fixed p/sub x/ and p/sub m/.
机译：遗传算法（GA's）中调整交叉p / sub x /和突变p / sub m /的概率的研究是进化计算中最重要和最有希望的研究领域之一，因为p / sub x /和p / sub m /极大地决定了该算法是否会找到一个接近最佳的解决方案，或者它是否会有效地找到一个解决方案。代替固定的p / sub x /和p / sub m /，本工作介绍了使用模糊逻辑自适应地调整p / sub x /和p / sub m /，以在整个过程中优化电力电子电路。通过应用K均值算法，搜索空间中人口的分布在每个训练代中都被聚类。 p / sub x /和p / sub m /的推断由基于模糊的系统执行，该系统模糊了包含最佳和最差染色体的簇的相对大小。提出的自适应方法用于优化需要满足一些静态和动态要求的降压调节器。与使用固定p / sub x /和p / sub m /的GA相比，优化后的电路组件值，调节器的性能以及训练中的收敛速度得到了有利的提高。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号