A Reliable Computational Scheme for Stochastic Reaction–Diffusion Nonlinear Chemical Model

The main aim of this contribution is to construct a numerical scheme for solving stochastic time-dependent partial differential equations (PDEs). This has the advantage problems with positive solutions. provides conditions obtaining solutions, which existing Euler–Maruyama method cannot do. In addition, it more accurate than non-standard finite difference (NSFD) method. Theoretically, suggested current NSFD method, and its stability consistency analysis are also shown. applied linear scalar parabolic equation nonlinear auto-catalytic Brusselator model. deficiency in terms accuracy shown by providing different graphs. Many observable occurrences physical world can be traced back certain chemical concentrations. Examining understanding inter-diffusion between concentrations important, especially when they coincide. model gold standard describing relationship other variables systems. A computational code proposed may made available readers upon request convenience.