计算机工程与应用Issue(17)：108-111,4.DOI:10.3778/j.issn.1002-8331.1202-0182
基于模糊知识粒度的混合属性约简算法
Hybrid attribute reduction algorithm based on fuzzy knowledge granulation
曹月芹1
作者信息
- 1. 温州职业技术学院 计算机系，浙江 温州 325035
- 折叠
摘要
Abstract
In the real world there are massive, incomplete, vague, and inaccurate data or objects. As a result fuzzy information granulation has become a research trend in recent years. This paper defines a fuzzy knowledge granulation of fuzzy granular world by making use of fuzzy equivalence relation on the universe of discourse. Then it gives new rules of attribute reduction and a method of computing core attributes in order to preferably dig out some potential and valuable information. Because in a rough set model numerical attribute reduction usually brings information loss and fuzzy attributes are not taken into consider-ation, a heuristic algorithm for the reduction of hybrid decision system based on fuzzy knowledge granulation is proposed to eliminate the discretization process of continuous attributes, reduce the computational complexity and provide a unified approach for normal values and hybrid data. An example shows that the algorithm is effective.关键词
模糊等价关系/知识粒度/混合决策系统/属性约简Key words
fuzzy equivalence relation/knowledge granulation/hybrid decision system/attribute reduction分类
信息技术与安全科学引用本文复制引用
曹月芹..基于模糊知识粒度的混合属性约简算法[J].计算机工程与应用,2013,(17):108-111,4.
