Attribute reduction algorithm in random fuzzy information system based on belief measure and plausibility measure

In this paper, we propose a method of attribute reduction by introducing the concepts of belief measures and plausibility measures on attribute set of random fuzzy information system. Using this method, we propose an attribute reduction algorithm of random fuzzy information system. We also analyze t...

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Bibliographic Details
Published in2011 Eighth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) Vol. 1; pp. 361 - 365
Main Authors Xia Wu, Jialu Zhang, Xuegang Chen
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2011
Subjects
Algorithm
Approximation methods
Attribute reduction
Belief measures
Complexity theory
Educational institutions
Fuzzy sets
Information systems
Plausibility measures
Random fuzzy information systems
Rough sets
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Summary:In this paper, we propose a method of attribute reduction by introducing the concepts of belief measures and plausibility measures on attribute set of random fuzzy information system. Using this method, we propose an attribute reduction algorithm of random fuzzy information system. We also analyze the time complexity of algorithm and it is O(|U| 2| A|). Finally, the example illustrates that the algorithm is available.
ISBN:9781612841809
1612841805
DOI:10.1109/FSKD.2011.6019586