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An improved sparse identification of nonlinear dynamics with Akaike information criterion and group sparsity

A crucial challenge encountered in diverse areas of engineering applications involves speculating the governing equations based upon partial observations. On this basis, a variant of the sparse identification of nonlinear dynamics (SINDy) algorithm is developed. First, the Akaike information criteri...

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Detalles Bibliográficos
Autores principales: Dong, Xin, Bai, Yu-Long, Lu, Yani, Fan, Manhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9552166/
https://www.ncbi.nlm.nih.gov/pubmed/36246669
http://dx.doi.org/10.1007/s11071-022-07875-9