Fuzzy least square linear regression: a new approach
Publish place: 5th International Conference on Software Computing
Publish Year: 1402
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
CSCG05_012
تاریخ نمایه سازی: 9 اردیبهشت 1403
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.
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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