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- W2987662848 startingPage "109069" @default.
- W2987662848 abstract "Abstract The goal of this article is to make automatic data assimilation for a landslide tsunami model, given by the coupling between a non-hydrostatic multi-layer shallow-water and a Savage-Hutter granular landslide model for submarine avalanches. The coupled model is discretized using a positivity preserving second-order path-conservative finite volume scheme. Then, the data assimilation problem is posed in a global optimization framework. Later, multi-path parallel metaheuristic stochastic global optimization algorithms are developed. More precisely, a multi-path Simulated Annealing algorithm is compared with a multi-path hybrid global optimization algorithm based on coupling Simulated Annealing with gradient local searchers." @default.
- W2987662848 created "2019-11-22" @default.
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- W2987662848 date "2020-02-01" @default.
- W2987662848 modified "2023-10-02" @default.
- W2987662848 title "Global optimization for data assimilation in landslide tsunami models" @default.
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- W2987662848 doi "https://doi.org/10.1016/j.jcp.2019.109069" @default.
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