Mathematical Modelling and Computer Simulation
- *Corresponding Author:
- Huang Y
School of mathematics and information science
Anshan Normal University, Anshan, 114005, P. R. China
Tel: +86 0412 2960120
E-mail: [email protected]
Received Date: February 15, 2016; Accepted Date: February 24, 2016; Published Date: March 01, 2016
Citation: Huang Y, Zhang H, Laibin G (2016) Mathematical Modelling and Computer Simulation. J Appl Computat Math 5:291. doi:10.4172/2168-9679.1000291
Copyright: © 2016 Huang Y, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
This article adopts and analyzes a stochastic collocation method to approximate the solution of four order elliptic partial differential equations with random coefficients and forcing terms, which are applied for some mathematicalbiology model. The method is composed of a Galerkin finite approximation in space and a collocation in the zeros of suitable tensor product orthogonal polynomials (Gauss points) in the probability space, and natural brings on the solution of uncoupled deterministic problems. The well-posedness of the elliptic partial differential equations is investigated as well under some regular assumptions. Strong error estimates for the fully discrete solution using L2 norms are obtained in this work.