Approximate solutions by artificial neural network of hybrid fuzzy differential equations

In this article, we propose a new approach to solve the hybrid fuzzy differential equations based on the feed-forward neural networks. We first replace it by a system of ordinary differential equations. A trial solution of this system involves two parts. The first part satisfies the initial condition and contains no adjustable parameters; however, the second part involves a feed-forward neural network containing adjustable parameters (the weights). This method shows that using neural networks provides solutions with good generalization and the high accuracy.