Affiliations: [a] School of Computer Science and Engineering, Northwest Normal University, Lanzhou, Gansu, China
| [b] School of Economics and Management, Xidian University, Xi’an, Shaanxi, China
Correspondence:
[*]
Corresponding author. Qiang Zhang, School of Computer Science and Engineering, Northwest Normal University, Lanzhou, 730070, China. E-mail: [email protected].
Abstract: In 2020, the spread of the COVID-19 epidemic has attracted global attention. As a large-scale group that is receiving higher education, college students also show greater mood swings. How to reduce the psychological harm of anxiety to college students is a problem that needs to be solved urgently. Based on this, this paper proposes an evaluation model for the anxiety level of college students in different regions under the influence of COVID-19. First of all, the general influence index of college student’s anxiety level is obtained by correlation analysis. Secondly, the logical OR of the double quantization variable precision fuzzy set model and the degree fuzzy rough set model is used to establish the evaluation model of the anxiety level of college students under the influence of COVID-19. Finally, used big data, the idea of fuzzy upper and lower approximation, combined with the principle of maximum membership in fuzzy set theory, achieved the quantitative ranking of the anxiety levels of college students in different areas. The research shows that when the accuracy of decision-making is 45%, the anxiety level of the township college students group and the provincial capital or municipality college students group is higher. When the accuracy of decision-making is 65%, the anxiety level of the provincial capital or municipality college students group is higher than others.
Keywords: Fuzzy rough set, two universes, COVID-19, college students anxiety level
