JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2024, Vol. 59 ›› Issue (5): 114-130.doi: 10.6040/j.issn.1671-9352.7.2023.380

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Covering rough fuzzy sets and optimal scale selection in multi-scale decision systems

SHI Hongyi1,3, MA Zhouming1,2,3*   

  1. 1. School of Mathematics and Statistics, Minnan Normal University, Zhangzhou 363000, Fujian, China;
    2. Dgital Fujian Meteorological Big Data Research Institute(Minnan Normal University)Zhangzhou 363000, Fujian, China;
    3. Fujian Key Laboratory of Granular Computing and Application(Minnan Normal University), Zhangzhou 363000, Fujian, China
  • Published:2024-05-09

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Abstract: This paper extends the covering rough fuzzy set model by considering the membership degree of objects in the decision attribute in the neighborhood of the objects minimum description. Two different covering rough fuzzy set are proposed. Based on this, four covering rough set models in multi-scale decision systems are constructed by combining covering rough fuzzy sets with multi-scale decision systems. The corresponding positive region and attribute importance are defined, and the optimal scale selection algorithm is designed. Finally, comparative experiments compare the difference in regression prediction performance between the optimal scale selected by the four covering rough fuzzy set models in such multi-scale decision systems and the original scale. The experimental results indicate that the optimal scale combination selected by model four of covering rough fuzzy sets in multi-scale decision systems can effectively improve the predictive ability of the regression model.

Key words: rough fuzzy set, multi-scale decision system, optimal scale selection, regression prediction, minimum description

CLC Number: 

  • TP181
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