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This article is cited in 3 scientific papers (total in 3 papers)
Mathematical physics
Comparative analysis of gradient methods for source identification in a diffusion-logistic model
T. A. Zvonarevaa, O. I. Krivorot'koab a Novosibirsk State University
b Institute of Computational Mathematics and Mathematical Geophysics of Siberian Branch of Russian Academy of Sciences, Novosibirsk
Abstract:
The paper presents a comparative analysis of the numerical solution of the problem of source identification in the diffusion-logistics model from the data on the diffusion process at fixed points in time and space by gradient methods in continuous and discrete formulations. Expressions are obtained for calculating the gradient of the objective functional for two formulations related to the solution of the corresponding adjoint problems. It is shown that, if the discrete functions of the model are approximated by cubic splines, the accuracy of the solutions of the source identification problem has the same order in the case of continuous and discrete calculation of the gradient. Numerical experiments in solving the source identification problem for a discrete model of information dissemination in online social networks have shown that the use of the discrete approach significantly increases the computational time in comparison with the continuous approach.
Key words:
diffusion-logistic model, source identification problem, inverse problem, gradient methods, adjoint problem, comparative analysis, regularization, optimization, social processes.
Received: 10.08.2021 Revised: 10.08.2021 Accepted: 16.12.2021
Citation:
T. A. Zvonareva, O. I. Krivorot'ko, “Comparative analysis of gradient methods for source identification in a diffusion-logistic model”, Zh. Vychisl. Mat. Mat. Fiz., 62:4 (2022), 694–704; Comput. Math. Math. Phys., 62:4 (2022), 674–684
Linking options:
https://www.mathnet.ru/eng/zvmmf11390 https://www.mathnet.ru/eng/zvmmf/v62/i4/p694
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