Volume 7 Number 6 (Jun. 2012)
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JSW 2012 Vol.7(6): 1375-1384 ISSN: 1796-217X
doi: 10.4304/jsw.7.6.1375-1384

Dominance–based Rough Interval–valued Fuzzy Set in Incomplete Fuzzy Information System

Minlun Yan
Department of Mathematics and Applied Mathematics, Liangyungang Teacher’s College, Liangyungang, 222006, P.R. China

Abstract—The fuzzy rough set is a fuzzy generalization of the classical rough set. In the traditional fuzzy rough model, the set to be approximated is a fuzzy set. This paper deals with an incomplete fuzzy information system with interval-valued decision by means of generalizing the rough approximation of a fuzzy set to the rough approximation of an interval-valued fuzzy set. Since all condition attributes are considered as criteria in such incomplete fuzzy information system, the interval-valued fuzzy set is approximated by using the information granules, which are constructed on the basis of a dominance relation. By the proposed rough approximation, the “at least” and “at most” decision rules can be generated from the incomplete fuzzy information system with interval-valued decision. To obtain the optimal “at least” and “at most” decision rules, the concepts of the lower and upper approximate reducts, the relative lower and upper approximate reducts for an object are proposed in the incomplete fuzzy information system with intervalvalued decision. The judgement theorems and discernibility matrixes associated with these reducts are also obtained. Some numerical examples are employed to substantiate the conceptual arguments.

Index Terms—incomplete fuzzy information system, interval-valued fuzzy set, dominance relation, rough set theory, knowledge reduction, decision rule


Cite: Minlun Yan, "Dominance–based Rough Interval–valued Fuzzy Set in Incomplete Fuzzy Information System," Journal of Software vol. 7, no. 6, pp. 1375-1384, 2012.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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