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Öğe An application of artificial neural networks for solving fractional higher-order linear integro-differential equations(Springer, 2023) Allahviranloo, T.; Jafarian, A.; Saneifard, R.; Ghalami, N.; Nia, S. Measoomy; Kiani, F.; Fernandez-Gamiz, U.This ongoing work is vehemently dedicated to the investigation of a class of ordinary linear Volterra type integro-differential equations with fractional order in numerical mode. By replacing the unknown function by an appropriate multilayered feed-forward type neural structure, the fractional problem of such initial value is changed into a course of non-linear minimization equations, to some extent. Put differently, interest was sparked in structuring an optimized iterative first-order algorithm to estimate solutions for the origin fractional problem. On top of that, some computer simulation models exemplify the preciseness and well-functioning of the indicated iterative technique. The outstanding accomplished numerical outcomes conveniently reflect the productivity and competency of artificial neural network methods compared to customary approaches.
