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Fuzzy least square linear regression: a new approach

Publish Year: 1402
Type: Conference paper
Language: English
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CSCG05_012

Index date: 28 April 2024

Fuzzy least square linear regression: a new approach abstract

A significant amount of study has been done in a variety of domains on the problem of the distance between triangular fuzzy numbers. In this research, we present a fuzzy regression model, develop a new distance that can be used to measure the relationship between triangular fuzzy numbers, and integrate the least absolute deviation approach with the new distance. By translating this model into linear programming, we are able to more thoroughly explore its features and model technique. In addition, we look at the characteristics of the fuzzy least absolute linear regression model. In addition, we present some comparisons with several pre-existing fuzzy regression models and prove the reasonableness of our suggested model via the use of three numerical instances. In the end, we analyze the robust characteristic of the model that we have suggested and apply our model to the data set that is missing in order to validate the model data.

Fuzzy least square linear regression: a new approach Keywords:

Fuzzy least square linear regression: a new approach authors

Zahra Behdani

Department of mathematics and statistics, Behbahan Khatam Alanbia university of technology, Khouzestan, Iran

Majid Darehmiraki

Department of mathematics and statistics, Behbahan Khatam Alanbia university of technology, Khouzestan, Iran