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

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  • Hongwei Wang

    (Faculty of Mathematics and Computer Science, Quanzhou Normal University, Quanzhou 362000, China
    Fujian Provincial Key Laboratory of Data-Intensive Computing, Quanzhou 362000, China
    Fujian University Laboratory of Intelligent Computing and Information Processing, Quanzhou 362000, China)

  • Huilai Zhi

    (Faculty of Mathematics and Computer Science, Quanzhou Normal University, Quanzhou 362000, China
    Fujian Provincial Key Laboratory of Data-Intensive Computing, Quanzhou 362000, China
    Fujian University Laboratory of Intelligent Computing and Information Processing, 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
    Fujian Provincial Key Laboratory of Data-Intensive Computing, Quanzhou 362000, China
    Fujian University Laboratory of Intelligent Computing and Information Processing, Quanzhou 362000, China)

  • Jianbing Xiahou

    (Faculty of Mathematics and Computer Science, Quanzhou Normal University, Quanzhou 362000, China
    Fujian Provincial Key Laboratory of Data-Intensive Computing, Quanzhou 362000, China
    Fujian University Laboratory of Intelligent Computing and Information Processing, Quanzhou 362000, China)

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.

Suggested Citation

  • Hongwei Wang & Huilai Zhi & Yinan Li & Daxin Zhu & Jianbing Xiahou, 2025. "A Generalized Multigranulation Rough Set Model by Synthesizing Optimistic and Pessimistic Attitude Preferences," Mathematics, MDPI, vol. 13(9), pages 1-24, April.
    • Handle: RePEc:gam:jmathe:v:13:y:2025:i:9:p:1367-:d:1639970
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