Selected article for: "neural network and quarantine policy"

Author: Raj Dandekar; George Barbastathis
Title: Quantifying the effect of quarantine control in Covid-19 infectious spread using machine learning
  • Document date: 2020_4_6
  • ID: 222c1jzv_41
    Snippet: Forecasts in figures 3, 5, 7 were obtained by using the sub-population data on the final days of their respective training periods to initialize the trained neural network models for Wuhan, Italy and Korea. For figure 10 , the forecasts were obtained by similarly initializing the model but subsequently in the post April 1 st period adjusting the quarantine model gradually over 17 days till 10 April according to where j = Wuhan, Italy, Korea for t.....
    Document: Forecasts in figures 3, 5, 7 were obtained by using the sub-population data on the final days of their respective training periods to initialize the trained neural network models for Wuhan, Italy and Korea. For figure 10 , the forecasts were obtained by similarly initializing the model but subsequently in the post April 1 st period adjusting the quarantine model gradually over 17 days till 10 April according to where j = Wuhan, Italy, Korea for the respective assumed quarantine policy adoptions.

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