HIGHLIGHTS
SUMMARY
Ardabili et_al used genetic algorithms, particle swarm optimization algorithms, and gray wolf optimizer to estimate parameters in prediction models such as power functions, and used two machine_learning algorithms to directly predict the infected cases, and the prediction results obtained were more accurate than prediction models such as power functions. Other factors such as machine_learning methods can be introduced to expand the model. The authors established a nested model to incorporate machine_learning methods including Nonautoregressive (NAR) and Long-short term memory (LSTM) models respectively in the mechanism model (SIR model) to fit the β. The combined . . .
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