A three-phase method for spherical fuzzy environment and application to community epidemic prevention management. (January 2023)

• Record Type: Journal Article
• Authors: Li, Zengxian; Liu, Aijun; Miao, Jie; Yang, Yun
• Is Part Of: Expert systems with applications. Volume 211(2023)
• Publication Date: 2023-01
• Subjects: Spherical fuzzy sets -- Multi-attribute group decision making -- VIKOR method -- Normalized projection -- Community-based epidemic prevention and control assessment method; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2022.118601
• Languages: English
• ISSNs: 0957-4174

Abstract

Highlights: A normalized projection measure is proposed in spherical fuzzy sets. A modified entropy measure is defined in spherical fuzzy sets. A nonlinear programming model is constructed to obtain attribute weights. An extended VIKOR method is proposed to obtain the ranking of alternatives. Abstract: As the basic unit of urban governance, communities play an important role in the prevention and control of epidemics. Appropriate methods for assessing the status of community-based epidemic prevention and control will not only help to gain a comprehensive understanding of community preparedness, but also help the government to develop appropriate epidemic prevention strategies. A three-phase multi-attribute group decision extension VIKOR method based on spherical fuzzy normalized projection is proposed for the dilemma of community-based epidemic prevention and control assessment method selection. Meanwhile, a knowledge-based spherical fuzzy entropy measure is proposed to determine the expert weights, and a nonlinear programming model based on the extended spherical fuzzy normalized projection TOPSIS method is given to obtain the attribute weights. In addition, an example of community-based epidemic prevention and control is given to demonstrate the feasibility of the proposed approach. Subsequently, compared with the traditional methods, it is found that there are differences in the ranking of alternatives obtained by the method in this paper and those obtained by other methods, but the optimal solution obtained is the same. Dynamic analysis by adjusting relevant parameters and expert evaluation information reveals that changes in parameters and deviations in individual expert information have little effect on the final results, which further illustrates the stability of the proposed method.