Mathematical Methods in the Applied Sciences · 2021 · 75 citations · 28 references
Natural SciencesComputational EngineeringComputational MechanicsDifferential EquationsStochastic ProcessesFinite Difference MethodsNumerical AnalysisNumerical Methods For Differential EquationsSimulation MethodsStochastic Differential EquationsFinite Difference DiscretizationFinite Difference SchemesFinite Difference SimulationInterpolation By Radial Basis FunctionsNonlinear Differential-algebraic EquationsNonlinear System ModelingNumerical Methods For Stochastic Differential EquationsTime Discretization
In this article, we introduce a numerical procedure to solve time‐fractional stochastic sine‐Gordon equation. The suggested technique is based on finite difference method and radial basis functions interpolation. By using this algorithm, first time‐fractional stochastic nonlinear sine‐Gordon equation is converted to elliptic stochastic differential equations. Then, the meshfree method based on radial basis functions (RBFs) is used to approximate the obtained equation. In fact, the finite difference method is used to approximate the unknown function in the time direction and generalized Gaussian RBF is applied to estimate the obtained equation in the space direction. The most important advantage of this method is that the noise terms are simulated directly at the collocation points at each time step. By employing this method, the equation decreased to a nonlinear system of algebraic equations which can be solved simply. The obtained results of solving three examples confirm the validity and capability of the proposed solution.
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Theory and applications of the sine-gordon equation
A. Barone, Francesco Esposito, C. J. Magee et al. · Rivista Del Nuovo Cimento · 1971 · 458 citations
Sharmila Karumuri, Rohit Tripathy, Ilias Bilionis et al. · Journal of Computational Physics · 2019 · 160 citations · Full text
Natural Sciences, Computational Engineering, Mathematics +13