• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

计算机工程与科学 ›› 2021, Vol. 43 ›› Issue (12): 2231-2237.

• 人工智能与数据挖掘 • 上一篇    下一篇

多源覆盖信息系统下的加权广义多粒度粗糙集模型及其应用

骆公志,陈佳馨   

  1. (南京邮电大学管理学院,江苏 南京210003)
  • 收稿日期:2020-07-20 修回日期:2020-09-06 接受日期:2021-12-25 出版日期:2021-12-25 发布日期:2021-12-31
  • 基金资助:
    国家自然科学基金(72171124,71771126);江苏高校哲学社会科学研究重大项目(2021SJZDA129);江苏省高校哲学社会科学优秀创新团队培育点资助项目(2017ZSTD022);江苏省研究生科研创新计划资助项目(KYCX19_0994)

A weighted generalized multi-granulation rough set model of multi-source covering information system and its applications

LUO Gong-zhi,CHEN Jia-xin   

  1. (College of Management,Nanjing University of Posts and Telecommunications,Nanjing 210003,China)
  • Received:2020-07-20 Revised:2020-09-06 Accepted:2021-12-25 Online:2021-12-25 Published:2021-12-31
  • Supported by:

摘要: 考虑到多源覆盖信息系统中数据的复杂性以及单个信息系统之间的不平等性,引入诱导覆盖粗糙集,并对信息系统的属性赋予权重值,提出了多源覆盖信息系统下的加权广义多粒度粗糙集MCS-WGMRS模型。定义了属性权重的计算方法,给出模型的上、下近似,并获取了相应的决策规则。通过实例分析验证了MCS-WGMRS模型的有效性,结果表明该模型对目标集的分类能力更强,适当调整阈值可进一步提高模型的容错性。

关键词: 多源信息系统, 广义多粒度, 覆盖粗糙集

Abstract: Considering the complexity of data in multi-source covering information systems and the inequality between individual information systems, this paper introduces the induced covering rough set and assigns weight values to each single information system’s attribute, and, consequently, proposes a weighted generalized multi-granulation rough set of multi-source covering information systems. Firstly, it defines the calculation method of attribute’s weight. Then, it gives complete upper and lower approximations of the model, and acquires the corresponding decision rule. Finally, it verifies the validity of the model through an example analysis. The experimental results show that the model has a better ability to classify the target set, and its fault tolerance can be further improved with appropriate adjustment of the threshold.


Key words: multi-source information system, generalized multi-granulation, covering rough set