A hybrid deep learning optimization for predicting the spread of a new emerging infectious disease
Faulinda Ely Nastiti,
Shahrulniza Musa,
Eiad Yafi
Abstract:<span lang="EN-US">In this study, a novel approach geared toward predicting the estimated number of coronavirus disease (COVID-19) cases was developed. Combining long short-term memory (LSTM) neural networks with particle swarm optimization (PSO) along with grey wolf optimization (GWO) employ hybrid optimization algorithm techniques. This investigation utilizes COVID-19 original data from the Ministry of Health of Indonesia, period 2020-2021. The developed LSTM-PSO-GWO hybrid optimization algorithm can i… Show more
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