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  • 标题:Rough set model based on variable universe
  • 本地全文:下载
  • 作者:Qingzhao Kong ; Xueer Chang
  • 期刊名称:CAAI Transactions on Intelligence Technology
  • 电子版ISSN:2468-2322
  • 出版年度:2022
  • 卷号:7
  • 期号:3
  • 页码:503-511
  • DOI:10.1049/cit2.12064
  • 语种:English
  • 出版社:IET Digital Library
  • 摘要:Abstract Rough set theory has a very good effect in information processing and knowledge discovery. In an information table, the current scholars regard all objects as a universe, and then establish various rough set models. However, in the analysis of many data problems, it is more reasonable to select parts of objects which are useful to us or can meet the actual needs as a universe. Therefore, in order to make up for the deficiency of traditional models, a new model is introduced from the perspective of variable universe. Then, some interesting properties of this model, such as approximation sets, reduct of attributes and maximum part of universe, are discussed. Through the study of this paper, it can be seen that the model developed in our paper is not only more accurate but also more effective in describing uncertain knowledge.
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