Descripción
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A preliminary version of a data driven reduced order model (ROM) for dynamical systems is presented in this Chapter. This ROM synergically and adaptively combines a black-box full model (FM) of the system and extrapolate conveniently using a recent extension of standard dynamic mode decomposition called higher order dynamic mode decom- position (HODMD). These two are applied in interspersed time inter- vals, called the FM-intervals and the HODMD-intervals, respectively. The data for the each HODMD-interval is obtained from the applica- tion of the FM in the previous FM-interval. The main question is when extrapolation from HODMD is no longer valid and switching to a new FM-interval is necessary. This is made attending to two criteria, ensuring that an estimate of the extrapolation error and a measure of consistency are both conveniently small. In this sense, the present method is similar to a previous method called POD on the Fly, which was not a purely data driven method. Instead, POD on the Fly was based on a Galerkin projection of the governing equations that thus should be known. The new method presented in this paper is illustrated with several transient dynamics for the complex Ginzburg-Landau equation that converges to either periodic or quasi-periodic attractors. The resulting CPU acceler- ations factors (compared to the full model) are quite large. | |
Internacional
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Si |
Nombre congreso
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14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019) |
Tipo de participación
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960 |
Lugar del congreso
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Sevilla |
Revisores
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Si |
ISBN o ISSN
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978-3-030-20054-1 |
DOI
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10.1007/978-3-030-20055-8 _ 54 |
Fecha inicio congreso
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13/05/2019 |
Fecha fin congreso
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15/05/2019 |
Desde la página
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567 |
Hasta la página
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576 |
Título de las actas
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Advances in Intelligent Systems and Computing |