A Generalized Multigranulation Rough Set Model by Synthesizing Optimistic and Pessimistic Attitude Preferences

Hongwei Wang, Huilai Zhi (), Yinan Li, Daxin Zhu and Jianbing Xiahou
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Hongwei Wang: Faculty of Mathematics and Computer Science, Quanzhou Normal University, Quanzhou 362000, China
Huilai Zhi: Faculty of Mathematics and Computer Science, Quanzhou Normal University, Quanzhou 362000, China
Yinan Li: Big Data Institute, Central South University, Changsha 410075, China
Daxin Zhu: Faculty of Mathematics and Computer Science, Quanzhou Normal University, Quanzhou 362000, China
Jianbing Xiahou: Faculty of Mathematics and Computer Science, Quanzhou Normal University, Quanzhou 362000, China

Mathematics, 2025, vol. 13, issue 9, 1-24

Abstract: Attitude preference plays an important role in multigranulation data mining and decision-making. That is, different attitude preferences lead to different results. At present, both optimistic and pessimistic multigranulation rough sets have been studied independently and thoroughly. But, sometimes, a decision-maker’s attitude may vary, which may shift either from an optimistic to pessimistic view of decision-making or from a pessimistic to optimistic view of decision-making. In this paper, we propose a novel multigranulation rough set model, which synthesizes optimistic and pessimistic attitude preferences. Specifically, we put forward methods to evaluate the attitude preferences in four types of decision systems. Two main issues are addressed with regard to attitude preference dependency. The first is concerned with the common attitude preference, while the other relates to the sequence-dependent attitude preference. Finally, we present three types of multigranulation rough set models from the perspective of the different connection methods between optimistic and pessimistic attitude preferences.

Keywords: rough set theory; granular computing; multigranulation rough set; attitude preference (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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