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  • 标题:Fuzzy-rough set models and fuzzy-rough data reduction
  • 本地全文:下载
  • 作者:Ghroutkhar, Alireza Mansouri ; Nehi, Hassan Mishmast
  • 期刊名称:Croatian Operational Research Review
  • 印刷版ISSN:1848-0225
  • 出版年度:2020
  • 卷号:11
  • 期号:1
  • 页码:67-80
  • DOI:10.17535/crorr.2020.0006
  • 出版社:Croatian Operational Research Society
  • 摘要:Rough set theory is a powerful tool to analysis the information systems. Fuzzy rough set is introduced as a fuzzy generalization of rough sets. This paper reviewed the most important contributions to the rough set theory, fuzzy rough set theory and their applications. In many real world situations, some of the attribute values for an object may be in the set-valued form. In this paper, to handle this problem, we present a more general approach to the fuzzification of rough sets. Specially, we define a broad family of fuzzy rough sets. This paper presents a new development for the rough set theory by incorporating the classical rough set theory and the interval-valued fuzzy sets. The proposed methods are illustrated by an numerical example on the real case.
  • 关键词:fuzzy rough set; lower approximation; upper approximation discernibility matrix
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