Attribute reduction in interval-valued fuzzy ordered decision tables via evidence theory

The Journal of Engineering

Weihua Xu¹  Jia Zhang²  Xiaoyan Zhang³ 

[1] School of Mathematics and Statistics, Southwest University , Chongqing, 400715 , People'School of Science, Chongqing University of Technology , Chongqing 400054 , People's Republic of China

关键词: evidence theory;    attribute reduction;    plausibility reducts;    interval-valued fuzzy ordered information system;    rough set theory;    interval-valued fuzzy ordered decision tables;    IVFODT;   

DOI  :  10.1049/joe.2018.8312

学科分类：工程和技术（综合）

来源: IET

【 摘 要 】

There are two different theory methods that are rough set theory and evidence theory, but these two theories can both handle some incomplete and uncertain information. In this study, these two models are combined in the interval-valued fuzzy ordered information system (IVFOIS). Belief functions and plausibility functions are proposed based on dominance relations in IVFOISs. The belief and plausibility reducts are defined in interval-valued fuzzy ordered decision tables (IVFODTs) and the attribute reduction of IVFODTs based on evidence theory is established. Finally, the authors use an instance to verify the above argument.

【 授权许可】

CC BY