Data analysis and forecast of Covid-19 cases in the Madre de Dios Department of Peru using LSTM techniques
DOI:
https://doi.org/10.55873/rad.v1i2.195Keywords:
Covid-19, LSTM, infected, pandemic, forecastAbstract
Currently, Covid-19 is causing great losses worldwide, which is why different works that allow predicting or forecasting the behavior of the number of infected using forecasting techniques within the Artificial Intelligence field are allowing control measures to be taken in the different countries. In this work, a deep learning model was proposed to forecast daily cases in the regions of Madre de Dios. The data used belongs to the covid-19 open data set, from the Peruvian Ministry of Health (MINSA). The data set includes the periods from the beginning of March 2020 to the end of December 2021. An LSTM was used using variables of Date, Department, Province, District, Cases, IP. ID and with a window size of 5 days, an accuracy of 94.67% was obtained with the training data and 92.31%.
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Copyright (c) 2022 Jose Carlos Navarro-Vega, Nelly Jacqueline Ulloa-Gallardo, Diego Raphael Paz-Bustamante, Diego Gustavo Zegarra-Conde, Wilder Nina-Choquehuayta
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