Rough Set Weighting

Rough Set Weighting is a criteria weighting method that determines attribute significance in decision-making systems by analyzing inherent data patterns and dependencies through the mathematical framework of rough set theory, without requiring prior knowledge or external preferences.

42

Publications

1.3K

Citations

126

Authors

66

Institutions

Publications per year

2017–2026

18

Authors

126

  1. XB
    Xinzhong Bao

    Beijing Union University, China

    2 publications · 27 citations

    2

    h-index

  2. QZ
    Qi Zhou

    Guangdong University of Technology, China

    1 publications · 31 citations

    1

    h-index

  3. YF
    Yaima Filiberto

    Universidad Central "Marta Abreu" de las Villas (UCLV), Cuba

    1 publications · 30 citations

    1

    h-index

  4. JL
    Jinyue Liu

    University of Shanghai for Science and Technology, China

    1 publications · 31 citations

    1

    h-index

  5. AT
    Ayşe Topal

    Niğde Ömer Halisdemir Üniversitesi, Türkiye

    1 publications · 15 citations

    1

    h-index

1–5 of 126

Venues

  1. Soft Computing

    2 publications · 31 citations

    2

    h-index

  2. Environmental Earth Sciences

    2 publications · 44 citations

    2

    h-index

  3. Information Sciences

    2 publications · 121 citations

    2

    h-index

  4. Applied Soft Computing

    2 publications · 127 citations

    2

    h-index

  5. IEEE Transactions on Fuzzy Systems

    TFS · 2 publications · 135 citations

    2

    h-index

1–5