Affiliations: [a] College of Information Science and Technology, Beijing Normal University, Beijing, P.R. China | [b] College of Mathematics and Information Science, Hebei Normal University, Shijiazhuang, P.R. China
Correspondence:
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Corresponding author. Wenyi Zeng, College of Information Science and Technology, Beijing Normal University, Beijing 100875, P.R. China. Tel.: +86 10 58805665; Fax: +86 10 58808313; E-mail: zengwy@bnu.edu.cn.
Abstract: In this paper, we propose a new similarity measure between generalized trapezoidal fuzzy numbers (GTFN), which can ensure the effectiveness of similarity measure, reduce the complexity of computation, and improve its distinguish ability and application scope. Meanwhile, we introduce two indexes to evaluate the performance of different similarity measures, and use numerical examples to compare our proposed similarity measure with some existing similarity measures. Finally, we apply our proposed similarity measure in fuzzy risk analysis, and the results show that our proposed similarity measure is reasonable and effective.
