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Identifiability analysis for source problem of quasi-hyperbolic equation Научная публикация

Конференция 5th International Conference on Problems of Cybernetics and Informatics
28-30 авг. 2023 , Баку
Сборник 2023 5th International Conference on Problems of Cybernetics and Informatics (PCI)
Сборник, IEEE. 2023. ISBN 979-8-3503-1907-1.
Вых. Данные Год: 2023, Страницы: 1-4 Страниц : 4 DOI: 10.1109/PCI60110.2023.10325964
Ключевые слова identifiability, sensitivity analysis, source problem, inverse problem, optimization, regularization, diffusion-logistic model
Авторы Zvonareva Tatiana 1,2 , Krivorotko Olga 1,3
Организации
1 Sobolev Institute of Mathematics SB RAS
2 Novosibirsk State University
3 Yugra University

Информация о финансировании (1)

1 Министерство науки и высшего образования РФ FENG-2023-0004

Реферат: The source for a quasi-hyperbolic equation with a small parameter before the second derivative in time using additional measurements of integral type in fixed times is investigated. The source is parametrized by 6 constants. A sensitivity-based identifiability analysis of the source problem is carried out using the Sobol method. It is shown that all investigated source parameters are not enough sensitive to the additional measurements. The source problem has been reduced to a misfit function minimization problem and solved by the tensor train global optimization method. For 6 parameters it is shown that the smallest error value of the reconstruction of the required parameters is achieved in the case of non-zero small parameter. The reducing of the number of parameters to 3 is a regularization.
Библиографическая ссылка: Zvonareva T. , Krivorotko O.
Identifiability analysis for source problem of quasi-hyperbolic equation
В сборнике 2023 5th International Conference on Problems of Cybernetics and Informatics (PCI). – IEEE., 2023. – C.1-4. – ISBN 979-8-3503-1907-1. DOI: 10.1109/PCI60110.2023.10325964 Scopus OpenAlex
Даты:
Опубликована в печати: 27 нояб. 2023 г.
Опубликована online: 27 нояб. 2023 г.
Идентификаторы БД:
Scopus: 2-s2.0-85179896046
OpenAlex: W4389041991
Цитирование в БД: Пока нет цитирований
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