Granular Space Reduction to a β Multigranulation Fuzzy Rough Set

被引：0
|
作者：
Zhou, Junyi [1 ]
Ma, Shaohui [1 ,2 ]
Li, Jianzhen [3 ]
机构：
[1] Jiangsu Univ Sci & Technol, Sch Econ & Management, Zhenjiang 212003, Peoples R China
[2] Nanjing Univ Sci & Technol, Key Lab Intelligent Percept & Syst High Dimens In, Minist Educ, Nanjing 210094, Jiangsu, Peoples R China
[3] Jiangsu Univ Sci & Technol, Sch Elect & Informat, Zhenjiang 212003, Peoples R China
来源：
ABSTRACT AND APPLIED ANALYSIS | 2014年
基金：
中国国家自然科学基金;
关键词：
D O I：
10.1155/2014/679037
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
Multigranulation rough set is an extension of classical rough set, and optimistic multigranulation and pessimistic multigranulation are two special cases of it beta multigranulation rough set is a more generalized multigranulation rough set. In this paper, we first introduce fuzzy rough theory into beta multigranulation rough set to construct a beta multigranulation fuzzy rough set, which can be used to deal with continuous data; then some properties are discussed. Reduction is an important issue of multigranulation rough set, and an algorithm of granular space reduction to beta multigranulation fuzzy rough set for preserving positive region is proposed. To test the algorithm, experiments are taken on five UCI data sets with different values of beta The results show the effectiveness of the proposed algorithm.
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页数：7
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