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.
Description
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