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Prediction of hierarchical time series using structured regularization and its application to artificial neural networks

This paper discusses the prediction of hierarchical time series, where each upper-level time series is calculated by summing appropriate lower-level time series. Forecasts for such hierarchical time series should be coherent, meaning that the forecast for an upper-level time series equals the sum of...

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Detalles Bibliográficos
Autores principales: Shiratori, Tomokaze, Kobayashi, Ken, Takano, Yuichi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7660543/
https://www.ncbi.nlm.nih.gov/pubmed/33180811
http://dx.doi.org/10.1371/journal.pone.0242099

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