Chargement en cours...
Comparison of ARIMA and LSTM in Forecasting the Incidence of HFMD Combined and Uncombined with Exogenous Meteorological Variables in Ningbo, China
Background: This study intends to identify the best model for predicting the incidence of hand, foot and mouth disease (HFMD) in Ningbo by comparing Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory Neural Network (LSTM) models combined and uncombined with exogenous meteoro...
Enregistré dans:
| Publié dans: | Int J Environ Res Public Health |
|---|---|
| Auteurs principaux: | , , , , , , , , |
| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
MDPI
2021
|
| Sujets: | |
| Accès en ligne: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8201362/ https://ncbi.nlm.nih.gov/pubmed/34200378 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/ijerph18116174 |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|