Novel Recurrent neural networks for efficient heat transfer analysis in radiative moving porous triangular fin with heat generation

Novel Recurrent neural networks for efficient heat transfer analysis in radiative moving porous triangular fin with heat generation

This paper investigates the use of Artificial Intelligence (AI), notably Recurrent Neural Networks (RNNs), to analyze heat transfer in moving radiative porous triangular systems with heat generation (HTMPTHG). AI-based RNN models are employed to simulate and forecast the complex heat transfer behavi...

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Bibliographic Details
Main Authors: Sana Ullah Saqib, Umar Farooq, Nahid Fatima, Yin-Tzer Shih, Ahmed Mir, Lioua Kolsi
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Case Studies in Thermal Engineering
Subjects:
Permeable fin in a triangle form
Convection radiation fin effectiveness
Recurrent neural networks (RNNs)
Lobatto III-A technique
AI-Based intelligent computing
Online Access:http://www.sciencedirect.com/science/article/pii/S2214157X24015478
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