On The Inverse Problem Of Time Dependent Coefficient In A Time Fractional Diffusion Problem By Newly Defined Monic Laquerre Wavelets

IF 1.9 4区 工程技术 Q3 ENGINEERING, MECHANICAL
M. Bayrak, Ali Demir
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引用次数: 0

Abstract

The primary aim of this research is to establish the time dependent diffusion coefficient in a one dimensional time fractional diffusion equation in Caputo sense by means of newly defined Monic Laquerre wavelets (MLW) and collocation points. We first give the definition of MLW by taking Monic Laquerre polynomials into account. Later, time fractional diffusion problem is reduced into a system of ordinary fractional and algebraic equations by utilizing MLW. Residual power series method and the over-measured data are applied to this system to determine the solution and the unknown time dependent coefficient together in series form. In the end, illustrative examples are presented to show the stability and accuracy of the proposed wavelet method for the inverse problem of determining unknown time dependent coefficient in fractional diffusion problems. The reliability of the proposed algorithm for the inverse problems is supported by high degree of accuracy in given examples.
用新定义的moniclaquerre小波研究时间分数阶扩散问题中时间相关系数的逆问题
本研究的主要目的是利用新定义的Monic Laquerre小波(MLW)和配点,建立一维时间分数扩散方程在Caputo意义下的时间相关扩散系数。我们首先通过考虑Monic Laquerre多项式给出了MLW的定义。然后,利用MLW将时间分数扩散问题简化为一个普通分数方程和代数方程系统。该系统采用残差幂级数法和过测数据,以级数形式共同确定解和未知时相关系数。最后,通过算例说明了所提小波方法求解分数阶扩散问题中未知时变系数逆问题的稳定性和准确性。所提算法在求解反问题时具有较高的精度,证明了算法的可靠性。
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来源期刊
CiteScore
4.00
自引率
10.00%
发文量
72
审稿时长
6-12 weeks
期刊介绍: The purpose of the Journal of Computational and Nonlinear Dynamics is to provide a medium for rapid dissemination of original research results in theoretical as well as applied computational and nonlinear dynamics. The journal serves as a forum for the exchange of new ideas and applications in computational, rigid and flexible multi-body system dynamics and all aspects (analytical, numerical, and experimental) of dynamics associated with nonlinear systems. The broad scope of the journal encompasses all computational and nonlinear problems occurring in aeronautical, biological, electrical, mechanical, physical, and structural systems.
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