Journal
INFORMATION SCIENCES
Volume 190, Issue -, Pages 1-16Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2011.12.006
Keywords
Fuzzy rough set; Neighborhood rough set; Hybrid data; Hybrid information granules; Granular computing
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Funding
- National Natural Science Foundation of China [71031006, 70971080, 60903110]
- Special prophase project for the National Key Basic Research and Development Program of China (973) [2011CB311805]
- Foundation of Doctoral Program Research of the Ministry of Education of China [20101401110002]
- Natural Science Foundation of Shanxi Province [2009021017-1, 2010021017-3]
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To discover knowledge from hybrid data using rough sets, researchers have developed several fuzzy rough set models and a neighborhood rough set model. These models have been applied to many hybrid data processing applications for a particular purpose, thus neglecting the issue of selecting an appropriate model. To address this issue, this paper mainly concerns the relationships among these rough set models. Investigating fuzzy and neighborhood hybrid granules reveals an important relationship between these two granules. Analyzing the relationships among rough approximations of these models shows that Hu's fuzzy rough approximations are special cases of neighborhood and Wang's fuzzy rough approximations, respectively. Furthermore, one-to-one correspondence relationships exist between Wang's fuzzy and neighborhood rough approximations. This study also finds that Wang's fuzzy and neighborhood rough approximations are cut sets of Dubois' fuzzy rough approximations and Radzikowska and Kerre's fuzzy rough approximations, respectively. (C) 2011 Elsevier Inc. All rights reserved.
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