A Multi-Layer Neural Network Approach for Solving Fractional Heat Equations

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Date

2025

Journal Title

Journal ISSN

Volume Title

Publisher

Toronto Metropolitan University

Abstract

In this study, a new multi-layer neural network (MLNN) approach designed to solve fractional heat equations (FHEs) is introduced. To handle the fractional derivative, the Laplace transform for approximation was applied. The results of our approach with those obtained using the finite difference method(FDM) are compared. The findings highlight the flexibility and computational efficiency of the proposed approach, making it a promising technique for solving FHEs. © 2025 Elsevier B.V., All rights reserved.

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Keywords

Adam Optimizer, Fractional Heat Equations, Laplace Transform, Neural Network

Turkish CoHE Thesis Center URL

WoS Q

N/A

Scopus Q

Q4

Source

International Conference on Thermal Engineering

Volume

1

Issue

1

Start Page

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