Abstract
In a covering decision system, the outside edge of attributes is not clear and the existing attribute reduction methods have limitations. In this paper, we first put forward the idea of fuzzy attribute; second, we determine the cover through a δ value, and further, we can give a method of attribute reduction by using the information entropy; finally, we compare our method with [15] through a practical case and prove that our reduction method is more practical than that of [15], and attribute reduction results vary with the standard of covering.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Pawlak Z (1998) Rough sets theory and its applications to data analysis. Cybern Syst 29:661–668
Ziarko W (1993) Variable precision rough set model. J Comput Syst Sci 46:39–59
Dubois D, Prade H (1992) Upper and lower images of a fuzzy set induced by a fuzzy relation. Inf Sci 64(3):203–232
Dubois D, Prade H (1990) Rough fuzzy sets and fuzzy rough sets. J Gen Syst 17:191–208
Morsi N, Yakout M (1998) Axiomatics for fuzzy rough sets. Fuzzy Sets Syst 100:327–342
Weizhi W, Jusheng M, Wenxiu Z (2003) Generalized fuzzy rough sets. Inf Sci 151:263–282
Jusheng M, Yee L, Huiyin Z, Tao F (2008) Generalized fuzzy rough sets determined by a triangular norm. Inf Sci 178:3203–3213
Zadeh LA (1965) Fuzzy sets. Inf Control 8:338–353
Zakowski W (1983) Approximations in the space. Demonstrate Math 16:761–769
Bonikowski Z (1998) Extensions and intention in the rough set theory. Inf Sci 107:149–167
Jun Z, Qingling Z, Wenshi C (2004) The fuzzy set subsystem based on the equivalent class. J Northeast Univ 25:731–733
William Z, Feiyue W (2003) Reduction and maximization of covering generalized rough sets. Inf Sci 152:217–230
Mordeson JN (2001) Rough set theory applied to ideal theory. Fuzzy Sets Syst 121:315–324
Degang C, Changzhong W, Qinghua H (2007) A new approach to attribute reduction of consistent and inconsistent covering decision systems with covering rough sets. Inf Sci 177:3500–3518
Fei L (2009) Approach to knowledge reduction of covering decision systems based on information theory. Inf Sci 179:1694–1704
Xiuyun X, Keyun Q (2011) Some notes on attribute reduction based on inconsistent covering decision system. Comput Eng Appl 47:97–101
Jun H, Guoyin W (2008) Hierarchical model of covering granular space. J Nanjing Univ 44:551–558
Qinghua H (2006) Fuzzy probabilistic approximation spaces and their information measures. IEEE Trans Fuzzy Syst 14:191–201
Acknowledgments
This work is supported by the National Natural Science Foundation of China (71071049) and the Natural Science Foundation of Hebei Province (F2011208056).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Li, F., Wang, J., Jin, C. (2014). A Method of Fuzzy Attribute Reduction Based on Covering Information System. In: Sun, F., Li, T., Li, H. (eds) Foundations and Applications of Intelligent Systems. Advances in Intelligent Systems and Computing, vol 213. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37829-4_40
Download citation
DOI: https://doi.org/10.1007/978-3-642-37829-4_40
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-37828-7
Online ISBN: 978-3-642-37829-4
eBook Packages: EngineeringEngineering (R0)