An Approach to Parameterized Approximation of Crisp and Fuzzy Sets

This paper proposes a concept of parameterized approximation of crisp and fuzzy sets, basing on the notion of rough and fuzzy rough inclusion function. A definition of a single e-approximation is given. It is suitable for expressing the lower and upper approximations defined in the rough set theory and the variable precision rough set model. A unified form of approximation is especially advantageous in the case of fuzzy information systems. It helps to avoid problems caused by different forms of fuzzy connectives used in the original definition of fuzzy rough sets. The presented parameterized approach to approximation constitutes an easy to implement, straightforward generalization of the variable precision crisp and fuzzy rough set model.

[1]  Wojciech Ziarko,et al.  Probabilistic Rough Sets , 2005, RSFDGrC.

[2]  Yiyu Yao,et al.  Rough Approximations under Level Fuzzy Sets , 2004, Rough Sets and Current Trends in Computing.

[3]  L. Kohout,et al.  FUZZY POWER SETS AND FUZZY IMPLICATION OPERATORS , 1980 .

[4]  Chris Cornelis,et al.  Sinha-Dougherty approach to the fuzzification of set inclusion revisited , 2003, Fuzzy Sets Syst..

[5]  Dominik Slezak,et al.  Variable Precision Bayesian Rough Set Model , 2003, RSFDGrC.

[6]  Salvatore Greco,et al.  Rough Membership and Bayesian Confirmation Measures for Parameterized Rough Sets , 2005, RSFDGrC.

[7]  Jesús Manuel Fernández Salido,et al.  Rough set analysis of a general type of fuzzy data using transitive aggregations of fuzzy similarity relations , 2003, Fuzzy Sets Syst..

[8]  Ramón Fuentes-González,et al.  Inclusion grade and fuzzy implication operators , 2000, Fuzzy Sets Syst..

[9]  Andrzej Skowron,et al.  Tolerance Approximation Spaces , 1996, Fundam. Informaticae.

[10]  Dominik Slezak,et al.  Rough Sets and Bayes Factor , 2005, Trans. Rough Sets.

[11]  Z. Pawlak Rough Sets: Theoretical Aspects of Reasoning about Data , 1991 .

[12]  Alicja Mieszkowicz-Rolka,et al.  Variable precision rough sets , 2003 .

[13]  Anna Maria Radzikowska,et al.  A comparative study of fuzzy rough sets , 2002, Fuzzy Sets Syst..

[14]  Alicja Mieszkowicz-Rolka,et al.  Variable Precision Fuzzy Rough Sets Model in the Analysis of Process Data , 2005, RSFDGrC.

[15]  Bernard De Baets,et al.  On rational cardinality-based inclusion measures , 2002, Fuzzy Sets Syst..

[16]  Wojciech Ziarko,et al.  Variable Precision Rough Set Model , 1993, J. Comput. Syst. Sci..

[17]  Salvatore Greco,et al.  Rough Set Processing of Vague Information Using Fuzzy Similarity Relations , 2000, Finite Versus Infinite.

[18]  Masahiro Inuiguchi Generalizations of Rough Sets: From Crisp to Fuzzy Cases , 2004, Rough Sets and Current Trends in Computing.

[19]  Lech Polkowski,et al.  Toward Rough Set Foundations. Mereological Approach , 2004, Rough Sets and Current Trends in Computing.

[20]  Didier Dubois,et al.  Putting Rough Sets and Fuzzy Sets Together , 1992, Intelligent Decision Support.

[21]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[22]  Wojciech Ziarko,et al.  Variable Precision Extension of Rough Sets , 1996, Fundam. Informaticae.