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Rough Set Construction and Entropy Weight Evaluation of Urban Higher Education Resource Carrying Capacity Based on Big Data

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  • Lulu Wang
  • Chao Liu
  • Muhammad Talha
  • Naeem Jan

Abstract

With the popularization of higher education, the scale of urban higher education continues to expand, and the contradiction between the supply and demand of educational resources becomes increasingly prominent, which restricts the steady development of urban higher education. Based on the rough set theory, this paper constructs a rough set of big data of urban higher education resource carrying capacity from the three levels of higher education core resources, urban economic resources and urban basic resources, and evaluates the entropy weight of the city where the university is located. According to the theoretical knowledge of higher education resource carrying capacity, the system deconstructs and expounds the balance mechanism of higher education resource carrying capacity, which provides solid theoretical support for the development of the paper. The research shows that the agglomeration development of higher education resources can improve the carrying capacity of urban higher education resources. The second section performed well on the whole, and the index distribution was more uniform. The third interval index structure distribution is complex and uneven, and the overall performance is general. The fourth section belongs to the poor section of educational carrying capacity with a low overall index. It can be seen that the carrying capacity of higher education resources varies significantly, which provides a scientific basis for improving the carrying capacity of higher education resources and theoretical and policy basis for realizing rational allocation and sustainable carrying capacity of higher education resources.

Suggested Citation

  • Lulu Wang & Chao Liu & Muhammad Talha & Naeem Jan, 2022. "Rough Set Construction and Entropy Weight Evaluation of Urban Higher Education Resource Carrying Capacity Based on Big Data," Journal of Mathematics, Hindawi, vol. 2022, pages 1-11, February.
  • Handle: RePEc:hin:jjmath:7776940
    DOI: 10.1155/2022/7776940
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