Geodesic
Selecting the most informative set of the deep-ocean tsunami sensors based on the r-solution method
Numerical methods and programming, Tome 23 (2022) no. 3, pp. 230-239.

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A significant constituent element of tsunami forecasting is to gain some insight into an initial tsunami waveform (below referred to as a tsunami source). Representing a tsunami source as a solution to the inverse problem of mathematical physics based on the inversion of remote records of the incoming wave allows one in detail to study the factors affected the inversion results. The above issue is an ill-posed one that causes the expected instability of the numerical solution. The regularization based on the truncated singular value decomposition (SVD) method (below referred to as the r-solution method) allows one to avoid this obstacle. Within the method proposed, we offer the methodology for selecting the most informative set of the tsunami sensors for the case of the Solomon Islands Tsunami of February 6, 2013, as an example. The method can be used in designing a tsunami warning system.
Mots-clés : tsunamis, singular value decomposition.
Keywords: numerical modeling, ill-posed problem 
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     title = {Selecting the most informative set of the deep-ocean tsunami sensors based on the r-solution method},
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     publisher = {mathdoc},
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     year = {2022},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/VMP_2022_23_3_a2/}
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T. A. Voronina; V. V. Voronin. Selecting the most informative set of the deep-ocean tsunami sensors based on the r-solution method. Numerical methods and programming, Tome 23 (2022) no. 3, pp. 230-239. http://geodesic.mathdoc.fr/item/VMP_2022_23_3_a2/