Authors: Stanojević, Bogdana 
Stanojević, Milan
Affiliations: Computer Science 
Mathematical Institute of the Serbian Academy of Sciences and Arts 
Title: Quadratic least square regression in fuzzy environment
Volume: 214
First page: 391
Last page: 396
Related Publication(s): Procedia Computer Science
Conference: 9th International Conference on Information Technology and Quantitative Management
Issue Date: 2022
Rank: M33
DOI: 10.1016/j.procs.2022.11.190
Abstract: 
The role of the regression analysis is crucial in many disciplines. Addressing the fuzzy quadratic least square regression for observed data modeled by fuzzy numbers, we aim to emphasize how a methodology that does not fully comply to the extension principle may fail to predict fuzzy valued numbers. We also propose a solution approach that functions in full accordance to the extension principle, thus overcoming the shortcomings arisen from the practice of splitting the optimization of a fuzzy number in independent optimizations of its components.
Keywords: Fuzzy regression | Fuzzy numbers | Extension principle
Publisher: Elsevier

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