Article Details

Abstract

For incomplete ordered information systems, under the extended dominance relation, the concepts of object dominance degree and object comprehensive dominance degree in a multi-granularity environment are defined respectively. Their properties are discussed, and a sorting method for objects in a multi-granularity environment is proposed. In addition, on the basis of the object comprehensive dominance degree and combined with the multi-granularity rough sets under the extended dominance relation, a method for objectively determining granularity weights is developed, which overcomes the subjectivity of traditional weight determination approaches. Through comparison, it is verified that the object sorting method and granularity weight method are extensions of the object sorting method and granularity weight method in single-granularity rough sets under the extended dominance relation.

Keywords

rough set theory; incomplete ordered information system; object dominance degree; granularity weight

References

1. [1] PAWLAK Z. Rough Sets [J].International Journal of Computer and Information Sciences，1982，11（5）：341-356.
2. [2] Zhang Wenxiu, Liang Yi, Wu Weizhi Information Systems and Knowledge Discovery [M]. Beijing: Science Press, 2003
3. [3] Zhang Wenxiu, Qiu Guofang Uncertain Decision Making Based on Rough Sets [M]. Beijing: Tsinghua University Press, 2005
4. [4] SHAO M W，ZHANG W X. Dominance Relation and Rules in an Incomplete Ordered Information System [J].International Journal of Intelligent Systems，2005，20：13-27.
5. [5] YANG X B，YANG J Y，WU C，et al. Dominance-Based Rough Set Approach and Knowledge Reductions in Incomplete Ordered Information System [J].Information Sciences，2008，178（4）：1219-1234.
6. [6] LUO G Z，YANG X B. Limited Dominance-Based Rough Set Model and Knowledge Reductions in Incomplete Decision System [J].Journal of Information Science and Engineering，2010，26：2199-2211.
7. [7] QIAN Y H，LIANG J Y，DANG C Y. Incomplete Multi-Granulation Rough Set [J].IEEE Transactions on Systems, Man and Cybernetics-Part A，2010，40（2）：420-431.
8. [8] QIAN Y H，LIANG J Y，YAO Y Y，et al. MGRS：A Multi-Granulation Rough Set [J].Information Sciences，2010，180（6）：949-970.
9. [9] Zhai Yongjian, Zhang Hong Multi granularity rough set of advantageous relationships in incomplete information systems [J]. Journal of Nanjing University of Science and Technology, 2012, 36 (1): 66-72
10. [10] XU W H，WANG Q R，ZHANG X T. Multi-Granulation Rough Sets Based on Tolerance Relations [J].Soft Computing，2013，17：1241-1252.
11. [11] ZHANG H D，ZHAN J M，HE Y P. Multi-Granulation Hesitant Fuzzy Rough Sets and Corresponding Applications [J].Soft Computing，2019，23（1）：13085-13103.
12. [12] Chen Wancui, Lv Yuejin, Weng Shizhou Sorting method based on tolerance advantage relationship and its application [J]. Computer Applications, 2014, 34 (8): 2170-2174
13. [13] Zhang Xiaoyan, Lei Liang, Xu Weihua Multi granularity modeling and object sorting method based on advantage relationship [J]. Journal of Hainan Tropical Ocean Institute, 2023, 30 (2): 73-83
14. [14] Lv Yuejin, Zhang Xuna, Wei Bipeng Weight determination of fuzzy comprehensive evaluation based on advantage relation rough set [J]. Statistics and Decision, 2012 (20): 44-46
15. [15] Xue Zhanao, Han Danjie, Lv Minjie, etc A new three branch decision model based on granularity importance [J]. Computer Science, 2019, 46 (2): 236-241
16. [16] Lu Jiaxue, Wang Xiaoyan Improvement of Granularity Importance Formula [J]. Journal of Suzhou University of Science and Technology: Natural Science Edition, 2021, 38 (4): 79-84

Funding

2023 Guangxi University Young and Middle aged Teachers Research Basic Ability Enhancement Project (2023KY10742023KY1081)

About the authors

Wei Bipeng (1987-), male, Dong ethnicity, from Guigang, Guangxi, associate professor, master's degree, research interests include rough set theory and its applications.