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Early prediction of coronavirus disease epidemic severity in the contiguous United States based on deep learning
I. Hsi Kao
,
Jau Woei Perng
*
*
此作品的通信作者
電控工程研究所
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引文 斯高帕斯(Scopus)
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Keyphrases
Deep Learning
100%
State-based
100%
Disease Outbreaks
100%
Confirmed Cases
100%
Coronavirus Disease (COVID)
100%
Early Prediction
100%
Contiguous United States
100%
Convolutional Autoencoder
100%
Long Short-term Memory
80%
Disease Prevention
40%
Centers for Disease Control
40%
United States
20%
World Health Organization
20%
Infectious Diseases
20%
Rapid Spread
20%
Mean Square Error
20%
Performance Prediction
20%
Peak Signal to Noise Ratio
20%
Structural Similarity Index
20%
COVID-19
20%
Epidemic Data
20%
Engineering
Autoencoder
100%
Deep Learning Method
100%
United States
100%
Long Short-Term Memory
80%
Mean Square Error
20%
Signal-to-Noise Ratio
20%
Structural Similarity
20%
Peak Signal
20%
Similarity Index
20%
World Health Organization
20%
Chemical Engineering
Long Short-Term Memory
100%
Deep Learning Method
100%
Material Science
Signal-to-Noise Ratio
100%