Comparative analysis in function approximation with neural networks and some basic polynomials

Kostadin Yotov, Emil Hadzhikolev, Stanka Hadzhikoleva, Margarita Terziyska

Abstract


Choosing the appropriate approximation method is a crucial step in solving a broad class of problems. It affects both the quality of the solutions obtained and the efficiency of the computational process. The article presents a study of various approximation cases with a specific group of polynomials and feedforward artificial neural networks. A comparative analysis of the results obtained has been conducted.

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