Solving Heat Transfer Equation by Using Feed Forward Neural Networks

  • Alaa Kamel Jaber
Keywords: Feed Forward Neural Network, Boundary-initial value problems, heat equation.

Abstract

The aim of this paper is to design feed forward neural network (FFNN) to solve the heat equation. Using a multi-layer with 7 hidden units (neurons) and one linear output unit, the sigmoid activation function of each unit in hidden layer is tansig function, where the Levenberg – Marquardt training algorithm is used to train the network .The existence of the proposed solution was proved. The suggested networks have been studied intensively for a few decades and have provided an option for modeling complex systems. Therefore this option was utilized to reduce the computation of solution, and finally the method is demonstrated through illustrative examples.

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Published
2017-07-22
How to Cite
Jaber, A. K. (2017). Solving Heat Transfer Equation by Using Feed Forward Neural Networks. Al-Qadisiyah Journal of Pure Science, 19(2), 163-172. Retrieved from https://journalsc.qu.edu.iq/index.php/JOPS/article/view/190
Section
Articles