An application of artificial neural networks for solving fractional higher-order linear integro-differential equations
Küçük Resim Yok
Tarih
2023
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
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.
Açıklama
Anahtar Kelimeler
Higher-Order Linear Integro-Differential Equation, Artificial Neural Network Approach, Caputo Fractional Derivative, Learning Algorithm, Cost Function
Kaynak
Boundary Value Problems
WoS Q Değeri
N/A
Scopus Q Değeri
Q3
Cilt
2023
Sayı
1
