TY - JOUR
T1 - Parameter and differentiation order estimation for a two dimensional fractional partial differential equation
AU - Aldoghaither, Abeer
AU - Laleg-Kirati, Taous-Meriem
N1 - KAUST Repository Item: Exported on 2020-10-01
PY - 2019/11/6
Y1 - 2019/11/6
N2 - This paper deals with the estimation of coefficients and differentiation orders for two-dimensional fractional partial differential equations. Recently, a hybrid method based on modulating functions has been proposed by the authors to estimate the coefficients and a differentiation order for a one dimensional fractional advection dispersion equation in Aldoghaither et al. (2015). We propose to extend this method to the two-dimensional case. First, the coefficients are estimated using a modulating functions method, where the problem is transferred into solving a system of algebraic equations. Then, the modulating functions method combined with a Newton algorithm is proposed to estimate the coefficients and the differentiation orders simultaneously. Numerical example is presented with noisy measurements to show the effectiveness and the robustness of the method.
AB - This paper deals with the estimation of coefficients and differentiation orders for two-dimensional fractional partial differential equations. Recently, a hybrid method based on modulating functions has been proposed by the authors to estimate the coefficients and a differentiation order for a one dimensional fractional advection dispersion equation in Aldoghaither et al. (2015). We propose to extend this method to the two-dimensional case. First, the coefficients are estimated using a modulating functions method, where the problem is transferred into solving a system of algebraic equations. Then, the modulating functions method combined with a Newton algorithm is proposed to estimate the coefficients and the differentiation orders simultaneously. Numerical example is presented with noisy measurements to show the effectiveness and the robustness of the method.
UR - http://hdl.handle.net/10754/659977
UR - https://linkinghub.elsevier.com/retrieve/pii/S0377042719305758
UR - http://www.scopus.com/inward/record.url?scp=85076214705&partnerID=8YFLogxK
U2 - 10.1016/j.cam.2019.112570
DO - 10.1016/j.cam.2019.112570
M3 - Article
SN - 0377-0427
VL - 369
SP - 112570
JO - Journal of Computational and Applied Mathematics
JF - Journal of Computational and Applied Mathematics
ER -