An Application of Granular Computing in Attribute Reduction Based on Rough Set Theory

摘要：

The rough set theory proposed by Pawlak is a new soft computing method and has become a hot topic in the field of knowledge discovery and decision-making. The problem of information granulation put forward by Zadeh in 1979 makes granular computing a new emerging concept and computing paradigm of information processing, and also hotspot in the artificial intelligence field. But so far, there is neither a general agreement about what is granular computing, nor a unified model This paper starts from the rough set theory, bases on the former research and brings forward a definition of granulation and a new reduction algorithm, then proves its validity by an example.

关键词： Rough set Granular computing Attribute reduction algorithm

作者: YU Shaoyang LUO Linkai

作者单位: Department of Automation University of Xiamen Xiamen,Fujian Province, China

会议类型: 国际会议

会议名称: 第一届国际计算机新科技与教育学术会议(Proceedings of the First International Conference on Computer Science & Education ICCSE2006)

会议地点: 厦门

会议语种:英文

页码: 772-774

在线出版日期: 2006-07-27（万方平台首次上网日期，不代表论文的发表时间）