Hesitant Fuzzy Linear Regression Model for Decision Making

An expert may experience difficulties in decision making when evaluating alternatives through a single assessment value in a hesitant environment. A fuzzy linear regression model (FLRM) is used for decision-making purposes, but this model is entirely unreasonable in the presence of hesitant fuzzy information. In order to overcome this issue, in this paper, we define a hesitant fuzzy linear regression model (HFLRM) to account for multicriteria decision-making (MCDM) problems in a hesitant environment. The HFLRM provides an alternative approach to statistical regression for modelling situations where input–output variables are observed as hesitant fuzzy elements (HFEs). The parameters of HFLRM are symmetric triangular fuzzy numbers (STFNs) estimated through solving the linear programming (LP) model. An application example is presented to measure the effectiveness and significance of our proposed methodology by solving a MCDM problem. Moreover, the results obtained employing HFLRM are compared with the MCDM tool called technique for order preference by similarity to ideal solution (TOPSIS). Finally, Spearman’s rank correlation test is used to measure the significance for two sets of ranking.

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The fuzzy linear regression model for finding sales forcastion from financial leasing in China’s equipment manufacturing industries

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-189667 ◽

2021 ◽

Vol 40 (4) ◽

pp. 8477-8484

Author(s):

Chengke Zhu ◽

Junshan Wang

Keyword(s):

Linear Regression ◽

Regression Model ◽

Linear Regression Model ◽

Substantial Effect ◽

Manufacturing Industries ◽

Fuzzy Linear Regression ◽

Sales Revenue ◽

Financial Leasing ◽

Equipment Manufacturing ◽

Fuzzy Linear Regression Model

With the development of technology and artificial intelligence(AI), financial leasing is used frequently in China’s equipment manufacturing industries, especially after 2008, which attracts our attention. This paper focuses on the problem. A theoretical model is provided in the paper to explain the motivation that why financial leasing is used in equipment manufacturing industries. In this paper, we employ multi-level fuzzy linear regression model to analyze data of manufacturing equipment industry of China in order to discover impact between sales revenue and financial leasing. We also discover credit sale forecasting using this model. We discover that economic leasing has a constructive important effect on sales revenue in total samples, which is consistent with the theoretical framework. However, the results are different in sub-industries, which shows that economic leasing has a constructive and important effect on sales profits in some sub-industries, but some of them are not. Furthermore, we also find that asset characteristics has a substantial effect on financial leasing decision. The outcome demonstrates that the more precise the asset, the easier it can be leased.

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