Approximations of Fuzzy Numbers by Using r - s Piecewise Linear Fuzzy Numbers Based on Weighted Metric

Haojie Lv and Guixiang Wang
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Haojie Lv: Institute of Operations Research and Cybernetics, Hangzhou Dianzi University, Hangzhou 310018, China
Guixiang Wang: Institute of Operations Research and Cybernetics, Hangzhou Dianzi University, Hangzhou 310018, China

Mathematics, 2022, vol. 10, issue 1, 1-17

Abstract: Using simple fuzzy numbers to approximate general fuzzy numbers is an important research aspect of fuzzy number theory and application. The existing results in this field are basically based on the unweighted metric to establish the best approximation method for solving general fuzzy numbers. In order to obtain more objective and reasonable best approximation, in this paper, we use the weighted distance as the evaluation standard to establish a method to solve the best approximation of general fuzzy numbers. Firstly, the conceptions of I -nearest r - s piecewise linear approximation (in short, PLA) and the II -nearest r - s piecewise linear approximation (in short, PLA) are introduced for a general fuzzy number. Then, most importantly, taking weighted metric as a criterion, we obtain a group of formulas to get the I -nearest r - s PLA and the II -nearest r - s PLA. Finally, we also present specific examples to show the effectiveness and usability of the methods proposed in this paper.

Keywords: approximations of fuzzy numbers; weighted metric; membership functions; r - s piecewise linear fuzzy number (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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