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. 2021 Jul 6;16(7):e0253925. doi: 10.1371/journal.pone.0253925

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© 2021 Davahli et al

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Fig 9 — The performance of deterministic and stochastic models trained on the COVID-19 cases dataset with seasonality and trend removed, in comparison to the original dataset in the leading state of California in group one: (a, c) performance of a deterministic model trained on the COVID-19 cases dataset (LSTM_1: without removal of seasonality and trend; LSTM_2: with removal of seasonality and trend), (b, d) performance of the stochastic model trained on the COVID-19 cases dataset (LSTM/MDN_1: without removal of seasonality and trend; LSTM/MDN_2: with removal of seasonality and trend).