Approximation Solution of Fractional Partial Differential Equations by Neural Networks

Abstract EN

Neural networks with radial basis functions method are used to solve a class of initial boundary value of fractional partial differential equations with variable coefficients on a finite domain.

It takes the case where a left-handed or right-handed fractional spatial derivative may be present in the partial differential equations.

Convergence of this method will be discussed in the paper.

A numerical example using neural networks RBF method for a two-sided fractional PDE also will be presented and compared with other methods.