Regional Economic Vitality Based on Weighted Grey Relational Analysis

Authors

  • Yi Liu North China University of Science and Technology Mathematical modeling Association(NCUSTMMA), North China University of Science and Technology, Tangshan, Hebei, 063000, China; School of Mining Engineering, North China University of Science and Technology, Tangshan, Hebei, 063000, China
  • Xiaoyu You North China University of Science and Technology Mathematical modeling Association(NCUSTMMA), North China University of Science and Technology, Tangshan, Hebei, 063000, China; School of Mechanical Engineering, Tangshan, North China University of Science and Technology, Tangshan, Hebei, 063000, China
  • Chunshuo Zhang School of Mechanical Engineering, Tangshan, North China University of Science and Technology, Tangshan, Hebei, 063000, China

DOI:

https://doi.org/10.30564/jesr.v3i2.1654

Abstract

Abstract: The future development of cities has a great relationship with economic vitality. To determine the size of the economic vitality and its main influencing factors. This article takes some cities in China as examples. First, determine the main factors. Aiming at many factors, this paper starts from the perspective of population changes in different cities and changes in corporate vitality. After applying the rough set theory to objectively evaluate index weights, the main factors are screened out. Then, the weights of the corresponding evaluation indexes of each group of cities are calculated by a multiple linear regression to a weighted index system, and then the cities are ranked using the gray correlation analysis method. Finally, we get the ranking of the economic vitality level of different cities. Finally, suggestions are made based on the weighting factors of major factors and economic vitality.

Keywords:

Rough set; Time series; Weighted grey correlation analysis; Economic vitality; Influencing factors

References

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Vol. 3 , Iss. 2 (April 2020)

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Articles

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