Approximation solution of fractional partial differential equations by neural networks (Q666395)

Summary: Neural networks with radial basis functions (RBFs) method are used to solve a class of initial boundary value of fractional partial differential equations (PDEs) 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 is discussed. A numerical example using neural networks RBF method for a two-sided fractional PDE also is presented and compared with other methods.