Identifiability analysis for source problem of quasi-hyperbolic equation Full article
| Conference |
5th International Conference on Problems of Cybernetics and Informatics 28-30 Aug 2023 , Баку |
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| Source | 2023 5th International Conference on Problems of Cybernetics and Informatics (PCI) Compilation, IEEE. 2023. ISBN 979-8-3503-1907-1. |
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| Output data | Year: 2023, Pages: 1-4 Pages count : 4 DOI: 10.1109/PCI60110.2023.10325964 | ||||||
| Tags | identifiability, sensitivity analysis, source problem, inverse problem, optimization, regularization, diffusion-logistic model | ||||||
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| Affiliations |
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Funding (1)
| 1 | Министерство науки и высшего образования РФ | FENG-2023-0004 |
Abstract:
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.
Cite:
Zvonareva T.
, Krivorotko O.
Identifiability analysis for source problem of quasi-hyperbolic equation
In compilation 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
Identifiability analysis for source problem of quasi-hyperbolic equation
In compilation 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
Dates:
| Published print: | Nov 27, 2023 |
| Published online: | Nov 27, 2023 |
Identifiers:
| Scopus: | 2-s2.0-85179896046 |
| OpenAlex: | W4389041991 |
Citing:
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