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

Ali, Amina HassanSenu, NorazakAhmadian, Ali2025-09-152025-09-1520252562-90342-s2.0-105012354565https://hdl.handle.net/20.500.14517/8379In 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.eninfo:eu-repo/semantics/closedAccessAdam OptimizerFractional Heat EquationsLaplace TransformNeural NetworkA Multi-Layer Neural Network Approach for Solving Fractional Heat EquationsConference ObjectN/AQ411