A Time-Series prediction model using longshort term memory networks for prediction of Covid – 19 data

Volume 19 No 7 (2021)

Dr.RohitaYamaganti , Dr.Gvani , S Ushamanjari

DOI: 10.48047/nq.2021.19.7.NQ21116

Abstract

This study proposes a time-series prediction model for Covid-19 data using LSTM networks. The model handles Covid-19 data's long-term relationships and irregular patterns to produce accurate and interpretable findings. The model is trained on a time-series dataset that includes information on the number of confirmed cases, deaths, and recoveries, as well as other relevant factors such as demographic information and social distancing policies

Keywords

Covid-19, time-series prediction, long-short term memory, LSTM, deep learning, forecasting, pandemic data, accuracy, ARIMA, Prophet, healthcare, resource allocation, intervention strategies

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