Fuzzy least square linear regression: a new approach

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.