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Journal of Applied Sciences
  Year: 2007 | Volume: 7 | Issue: 19 | Page No.: 2812-2817
DOI: 10.3923/jas.2007.2812.2817
 
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Feedforward Neural Network for Solving Partial Differential Equations
Mohsen Hayati and Behnam Karami

Abstract:
In this study a new method based on neural network has been developed for solution of differential equations. A modified neural network is used to solve the Burger’s equation in one-dimensional quasilinear partial differential equation. This method is generally applicable to nth order partial differential equations on a finite domain with boundary conditions. The results obtained by this method, have been compared with the exact solution and found to be in good agreement with each other and because of superior properties of neural network i.e., parallel processing thereby less computational cost, this method has advantages over conventional methods.
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How to cite this article:

Mohsen Hayati and Behnam Karami, 2007. Feedforward Neural Network for Solving Partial Differential Equations. Journal of Applied Sciences, 7: 2812-2817.

DOI: 10.3923/jas.2007.2812.2817

URL: https://scialert.net/abstract/?doi=jas.2007.2812.2817

 
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