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计算机工程 ›› 2007, Vol. 33 ›› Issue (18): 190-192,. doi: 10.3969/j.issn.1000-3428.2007.18.067

• 人工智能及识别技术 • 上一篇    下一篇

基于粗集理论的知识自动获取方法

刘道华1,2,原思聪1,李湘英2,王发展1   

  1. (1. 西安建筑科技大学机电学院,西安 710055;2. 信阳师范学院计算机科学系,信阳 464000)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2007-09-20 发布日期:2007-09-20

Method of Automatic Knowledge Gain Based on Rough Sets Theory

LIU Dao-hua1,2, YUAN Si-cong1, LI Xiang-ying2, WANG Fa-zhan1   

  1. (1. School of Mech. & Elec. Engineering, Xi’an University of Arch. & Technology, Xi’an 710055; 2. Dept. of Computer Science, Xinyang Normal University, Xinyang 464000)
  • Received:1900-01-01 Revised:1900-01-01 Online:2007-09-20 Published:2007-09-20

摘要: 分析了粗集理论的知识自动获取方法的基本原理和获取过程,研究了数据记录范化方法、属性归约算法、最小决策规则集的求解、规则提取方法,并给出了自动获取方法的实例。实例证明了该算法的有效性。

关键词: 粗糙集理论, 知识自动获取, 专家系统开发工具, 属性归约, 数据范化

Abstract: This paper analyzes the basic principle of automatic knowledge gaining method based on rough sets theory, introduces the automatic gaining process, and studies the method of data generalization, the concrete algorithm of the attribute reduction, solution of the smallest policy-making rule set and the method of decision-making rule. A concrete example is given about the knowledge’s automatic gaining method. The example shows the method is effective and feasible.

Key words: rough sets theory, knowledge automatic gain, development tool of expert system, attribute reduction, data generalization

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