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The approximate solution of one dimensional stochastic evolution equations by meshless methods | ||
| Journal of Mathematical Modeling | ||
| دوره 9، شماره 4، اسفند 2021، صفحه 599-609 اصل مقاله (608.48 K) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.22124/jmm.2021.18683.1598 | ||
| نویسندگان | ||
| Mahdi Jalili؛ Rezvan Salehi* | ||
| Department of Applied Mathematics, Faculty of Mathematical Sciences, Tarbiat Modares University, P.O. Box 14115-134, Tehran, Iran | ||
| چکیده | ||
| In this article, we develop an iterative scheme based on the meshless methods to simulate the solution of one dimensional stochastic evolution equations using radial basis function (RBF) interpolation under the concept of Gaussian random field simulation. We use regularized Kansa collocation to approximate the mean solution at space and the time component is discretized by the global $ \theta $-weighted method. Karhunen-lo\`{e}ve expansion is employed for simulating the Gaussian random field. Statistical tools for numerical analysis are standard deviation, absolute error, and root mean square. In this work, we solve two major problems for showing the convergence, and stability of the presented method on two problems. The first problem is the semilinear stochastic evolution problem, and the second one is stochastic advection-diffusion model with different control values. | ||
| کلیدواژه‌ها | ||
| Stochastic partial differential equation؛ Gaussian random field؛ Radial basis function؛ Regularized Kansa collocation؛ Reproducing kernel Hilbert space | ||
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آمار تعداد مشاهده مقاله: 728 تعداد دریافت فایل اصل مقاله: 653 |
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