Comparative Analysis of Picard and Adomian Decomposition Methods for Solving Fractional Differential Equations in a Neural Network Model

Document Type : Original research papers

Authors

1 Department of Basic science, Faculty of Engineering, Delta University for science and technology, Mansoura. Egypt,

2 Basic Science Department, Nile Higher Institute for Engineering and Technology, Mansoura, Egypt

Abstract

Various fields of science and engineering use neural network technology to solve their problems. In this paper, the Adomian decomposition method (ADM) is applied to solve fractional differential equations (FDEs) of a deferred correction network (DC Net) model using Caputo-Fabrizo (CF). To improve the accuracy of the calculated solution, we compare it with the Picard method (PM). It was found that the two schemes are very close to each other based on the analytical results. Comparing these two approaches, numerical tests confirm the accuracy of the proposed (DC Net) model.

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Delta University Scientific Journal
Volume 7, Issue 3
Special Issue DU- IECRI 2024 Second International Engineering Conference on Research and Innovation Faculty of Engineering, Delta University, Egypt
November 2024
Pages 281-290

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