Double-quantitative decision rough set over two universes and application to African swine fever decision-making. Issue 2 (4th March 2021)

• Record Type: Journal Article
• Authors: Hu, Xiaoyuan; Sun, Bingzhen; Wang, Ting; Jiang, Chao
• Is Part Of: Journal of experimental & theoretical artificial intelligence. Volume 33:Issue 2(2021)
• Page Start: 331
• Page End: 347
• Publication Date: 2021-03-04
• Subjects: African swine fever (ASF) decision making -- probabilistic graded rough set -- double quantitative information -- decision rough set; Artificial intelligence -- Periodicals; 006.3
• DOI: 10.1080/0952813X.2020.1744195
• Languages: English
• ISSNs: 0952-813X

Abstract

ABSTRACT: In order to actively respond to the severe situation of the current African swine fever (ASF) epidemic, this paper proposed a double-quantitative decision rough set method over two universes. First, a double-quantitative decision rough set model over two universes based on compatibility relation is defined. Furthermore, the characteristics of ASF decision-making problems are fully considered, and the ASF decision-making process is transformed into a rough approximation decision problem. Then, we construct a double-quantitative decision rough set application method over two universes based on ASF decision-making problems. The upper and lower approximations of the ASF decision objects are calculated by the double quantification approximation space over two universes, and the positive region of the ASF decision object is given. The model proposes a method of ASF decision-making and the optimal decision rules based on the personal preference information of decision-makers. Finally, the theoretical model is applied to the ASF decision problem to illustrate the application process and its effectiveness of the model constructed in this paper. At the same time, the corresponding decision suggestions for dealing with the actual ASF problem are proposed based on the application results of numerical examples.