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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 7-8/2013

01.06.2013 | Original Article

Fuzzy belief measure in random fuzzy information systems and its application to knowledge reduction

verfasst von: Jialu Zhang, Xiaoling Liu

Erschienen in: Neural Computing and Applications | Ausgabe 7-8/2013

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Abstract

In a random fuzzy information system, by introducing a fuzzy t-similarity relation on the objects set for a subset of attributes set, the approximate representations of knowledge are established. By discussing fuzzy belief measures and fuzzy plausibility measures defined by the lower approximation and the upper approximation in a random fuzzy approximation space, some equivalent conditions of knowledge reduction in a random fuzzy information system are proved. Similarly as in an information system, the fuzzy-set-valued attribute discernibility matrixes in a random fuzzy information system are constructed. Knowledge reduction is defined from the view of fuzzy belief measures and fuzzy plausibility measures and a heuristic knowledge reduction algorithm is proposed, and the time complexity of this algorithm is O(|U|2|A|). A running example illustrates the potential application of algorithm, and the experimental results on the data sets with numerical attributes show that the proposed method is effective.
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Metadaten
Titel
Fuzzy belief measure in random fuzzy information systems and its application to knowledge reduction
verfasst von
Jialu Zhang
Xiaoling Liu
Publikationsdatum
01.06.2013
Verlag
Springer-Verlag
Erschienen in
Neural Computing and Applications / Ausgabe 7-8/2013
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-012-0951-0

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