Generalized fuzzy rough sets

By Weizhi Wu, Jusheng Mi, Wenxiu Zhang. Information Sciences, 2003

601 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics

View Paper: https://www.semanticscholar.org/paper/e0684f7688e2181f7184b849b0cc2dfce3ca09e2

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Qinghua Hu
2. Daren Yu
3. Richard Jensen
4. Yiyu Yao
5. Zongxia Xie
6. Jiye Liang
7. Y. Qian
8. Chuangyin Dang

In Computational Theory and Mathematics

1. Qinghua Hu
2. Daren Yu
3. Richard Jensen
4. Zongxia Xie
5. Qiang Shen
6. Y. Qian
7. Jiye Liang
8. Yiyu Yao

Citations in the corpus

• Constructive and axiomatic approaches of fuzzy approximation operators (2004, methodology): “[35] illustrated that properties A RðRðAÞÞ and RðRðAÞÞ A do not hold for fuzzy rough approximation operators.”
• Computational Intelligence and Feature Selection - Rough and Fuzzy Approaches (2008, background): “[385] investigated the properties of generalized fuzzy-rough sets, defining a pair of dual generalized fuzzy approximation operators based on arbitrary fuzzy relations.”
• Information-preserving hybrid data reduction based on fuzzy-rough techniques (2006, methodology): “The properties and axiomatization of fuzzy rough set theory (Morsi and Yakout, 1998; Wu and Zhang, 2004; Wu et al., 2004) were analyzed in detail.”
• Attributes Reduction Using Fuzzy Rough Sets (2008, background): “These two approximation operators were studied in detail from the constructive and axiomatic approaches in [11], [12] with the properties (FP1)–(FP6).”
• Rudiments of rough sets (2007, unknown): “, [8,37,60,39,40,72,46,48,59,66,67,96,128,103, 127,134,136,139,148,149,157,189–196,207,208,216,219,229,230,232,236,244,245,251,265,188,279,281,286,288, 295,299,302,317,318,321–324,326,327,329,358–363,365,368]).”
• MGRS: A multi-granulation rough set (2010, background): “…been proposed in terms of various requirements, such as the variable precision rough set (VPRS) model (see [43]), the rough set model based on tolerance relation (see [7] [8] [9]), the Bayesian rough set model (see [33]), the fuzzy rough set model and the rough fuzzy set model (see [1] [34] [35]).”