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  • 标题:Novel Parameterized Utility Function on Dual Hesitant Fuzzy Rough Sets and Its Application in Pattern Recognition
  • 作者:Zhongjun Wu ; Zhongjun Wu ; Fangwei Zhang
  • 期刊名称:Information
  • 电子版ISSN:2078-2489
  • 出版年度:2019
  • 卷号:10
  • 期号:2
  • 页码:71
  • DOI:10.3390/info10020071
  • 语种:English
  • 出版社:MDPI Publishing
  • 摘要:Based on comparative studies on correlation coefficient theory and utility theory, a series of rules that utility functions on dual hesitant fuzzy rough sets (DHFRSs) should satisfy, and a kind of novel utility function on DHFRSs are proposed. The characteristic of the introduced utility function is a parameter, which is determined by decision-makers according to their experiences. By using the proposed utility function on DHFRSs, a novel dual hesitant fuzzy rough pattern recognition method is also proposed. Furthermore, this study also points out that the classical dual tool is suitable to cope with dynamic data in exploratory data analysis situations, while the newly proposed one is suitable to cope with static data in confirmatory data analysis situations. Finally, a medical diagnosis and a traffic engineering example are introduced to reveal the effectiveness of the newly proposed utility functions on DHFRSs.
  • 关键词:utility function; hesitant fuzzy rough set; correlation coefficient; traffic engineering; pattern recognition utility function ; hesitant fuzzy rough set ; correlation coefficient ; traffic engineering ; pattern recognition
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