Comparison of ARIMA and LSTM for prediction of hemorrhagic fever at different time scales in China.

PLoS One · 2022 · PMC8759700 · PMID 35030203

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a slightly increasing trendno p-value reported

The incidence of hemorrhagic fever in China has had a slightly increasing trend in recent years.

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a clear trendno p-value reported

The results show that ARIMA model tends to forecast more accurate results for which there is a clear trend in the series, whereas LSTM tends to do better on volatile time series with more instable components.

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