Predicting the New Cases of Coronavirus [COVID-19] in India by Using Time Series Analysis as Machine Learning Model in Python
| Autor: | Vikas Kulshreshtha, N. K. Garg |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
2019-20 coronavirus outbreak
General Computer Science Coronavirus disease 2019 (COVID-19) Computer science 020209 energy 02 engineering and technology Machine learning computer.software_genre Critical phase 0202 electrical engineering electronic engineering information engineering Autoregressive integrated moving average Electrical and Electronic Engineering Time series computer.programming_language Case Study Pandemic business.industry 020208 electrical & electronic engineering COVID-19 AR model Pneumonia Python (programming language) Predictive value Autoregressive model Cases Artificial intelligence ARIMA model business computer Python |
| Zdroj: | Journal of The Institution of Engineers (India): Series B |
| ISSN: | 2250-2114 2250-2106 |
| Popis: | Today world is going through a critical phase. The whole world is infected from the coronavirus [COVID 19]. In India also the number of new cases keeps on increasing. In this paper, the machine learning model has been developed using time series analysis (ARIMA model) for predicting the new cases in India in the next coming days. In this work, results are also compared with the predictive values generated from the ARIMA and AR model and concluded that the ARIMA model is the best fit model as compared to AR model for predicting the new cases in India. Python programming language has been used for implementation. The dataset from January 1, 2020 to July 31, 2020 has been taken for analysis. This paper is useful for researchers for further analysis of COVID-19 pandemic in India. |
| Databáze: | OpenAIRE |
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