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A meshless method based on the dual reciprocity method for one‐dimensional stochastic partial differential equations
Author(s) -
Dehghan Mehdi,
Shirzadi Mohammad
Publication year - 2016
Publication title -
numerical methods for partial differential equations
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.901
H-Index - 61
eISSN - 1098-2426
pISSN - 0749-159X
DOI - 10.1002/num.21995
Subject(s) - mathematics , partial differential equation , stochastic partial differential equation , reciprocity (cultural anthropology) , partial derivative , mathematical analysis , radial basis function , dual (grammatical number) , regularization (linguistics) , numerical partial differential equations , computer science , psychology , social psychology , art , literature , machine learning , artificial intelligence , artificial neural network
This article describes a new meshless method based on the dual reciprocity method (DRM) for the numerical solution of one‐dimensional stochastic heat and advection–diffusion equations. First, the time derivative is approximated by the time–stepping method to transforming the original stochastic partial differential equations (SPDEs) into elliptic SPDEs. The resulting elliptic SPDEs have been approximated with the new method, which is a combination of radial basis functions (RBFs) method and the DRM method. We have used inverse multiquadrics (IMQ) and generalized IMQ (GIMQ) RBFs, to approximate functions in the presented method. The noise term has been approximated at the source points, at each time step. The developed formulation is verified in two test problems with investigating the convergence and accuracy of numerical results. © 2015 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 32: 292–306, 2016