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模糊规则提取的两种方法性能分析
Performance Evaluation of Two Kinds of Rules Extracting Methods
【摘要】 机器学习近年来得到越来越多的重视,模糊规则提取是其中的重要的一个方向。本文介绍了两种自动提取模糊规则的方法,分别是基于多层前向网络和基于遗传算法的模糊规则自动生成。并且,详细的分析了两种方法性能
【Abstract】 In practice, the amount of sample data are becoming larger and larger, machine learning is a promising technology to solve such problem. We introduce two kinds of algorithm which is used to extract rules from sample data in this paper. And their detailed performance analysis of the result rules are described.
【关键词】 机器学习;
模糊规则;
多层前向网络;
遗传算法;
规则生成;
【Key words】 Machine Learning; Fuzzy Rule; Multilayer Feedforward Network; Genetic Algorithm; Rules Extracting;
【Key words】 Machine Learning; Fuzzy Rule; Multilayer Feedforward Network; Genetic Algorithm; Rules Extracting;
【基金】 国家863CIMS主题项目;国家经贸委资助项目
- 【文献出处】 模糊系统与数学 ,FUZZY SYSTEMS AND MATHEMATICS , 编辑部邮箱 ,1999年03期
- 【分类号】O159
- 【被引频次】20
- 【下载频次】234