Deep LSTM-Based Transfer Learning Approach for Coherent Forecasts in Hierarchical Time Series

Hierarchical time series is a set of data sequences organized by aggregation constraints to represent many real-world applications in research and the industry. Forecasting of hierarchical time series is a challenging and time-consuming problem owing to ensuring the forecasting consistency among the...

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Detalles Bibliográficos
Autores principales: Sagheer, Alaa, Hamdoun, Hala, Youness, Hassan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8271891/
https://www.ncbi.nlm.nih.gov/pubmed/34206750
http://dx.doi.org/10.3390/s21134379

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8271891/
https://www.ncbi.nlm.nih.gov/pubmed/34206750
http://dx.doi.org/10.3390/s21134379

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