Fuzzy multiple linear least squares regression analysis

Yingfang Li, Xingxing He, Xueqin Liu

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


In this paper, we construct a fuzzy multiple linear least squares regression model based on two distance measures between LR-type fuzzy numbers. The computational formulas for calculating regression parameters are presented. To evaluate the effectiveness of the proposed model, we define a similarity measure between LR-type fuzzy numbers and introduce two criteria called the error index and the similarity index, which respectively utilize distance measures and similarity measures between LR-type fuzzy numbers as measurements. In addition, we present two numerical examples with normal fuzzy numbers and triangular fuzzy numbers to demonstrate the performances of the proposed model.
Original languageEnglish
Pages (from-to)118-143
Number of pages6
JournalFuzzy Sets and Systems
Early online date07 Mar 2023
Publication statusPublished - 15 May 2023


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