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Predicting the number of new cases of COVID-19 in India using Survival Analysis and LSTM
5th International Conference on IoT in Social, Mobile, Analytics and Cloud (I-SMAC) ; : 290-293, 2021.
Article in English | Web of Science | ID: covidwho-1779072
ABSTRACT
COVID-19 has been the cause of death for thousands of people across the globe. The goal of this paper is to forecast the new COVID-19 cases in India. The other methods used to forecast COVID-19 cases fail to give results with good accuracy when they try to predict the new cases number for a long time period or when the count of daily cases reported is large since the population of a country is large. The proposed study overcomes the challenge by firstly customizing the dataset. Second, the survival analysis has been utilized to choose appropriate factors, and third, the data will be integrated into the Long Short-Term Memory Network (LSTM). With a mean absolute percentage error of 5.79 percent, data from the 30th of January, 2020, to the 16th of June, 2021, was used to determine the new cases number of even day for the next 21 days.
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Full text: Available Collection: Databases of international organizations Database: Web of Science Type of study: Prognostic study Language: English Journal: 5th International Conference on IoT in Social, Mobile, Analytics and Cloud (I-SMAC) Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Web of Science Type of study: Prognostic study Language: English Journal: 5th International Conference on IoT in Social, Mobile, Analytics and Cloud (I-SMAC) Year: 2021 Document Type: Article