Shapelet selection based on a genetic algorithm for remaining useful life prediction with supervised learning

RUL (remaining useful life) shapelets were recently developed to overcome the shortcomings of similarity-based RUL prediction methods, such as high sensitivity to parameters. RUL shapelets are informative subsequences whose distances to a run-to-failure time series sample are very useful for predict...

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Detalles Bibliográficos
Autores principales: Ahn, Gilseung, Jin, Min-Ki, Hwang, Seok-Beom, Hur, Sun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9791343/
https://www.ncbi.nlm.nih.gov/pubmed/36578413
http://dx.doi.org/10.1016/j.heliyon.2022.e12111

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9791343/
https://www.ncbi.nlm.nih.gov/pubmed/36578413
http://dx.doi.org/10.1016/j.heliyon.2022.e12111

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