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| COVID-19 Time Series Forecast Using Transmission Rate and Meteorological Parameters as Features | |
| Mousavi, Mohsen1,2; Holloway, Damien1; Gandomi, Amir H.2; Salgotra, Rohit3 | |
| 2020-10 | |
| 发表期刊 | IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE
 |
| ISSN | 1556-603X |
| EISSN | 1556-6048 |
| 摘要 | The number of confirmed cases of COVID-19 has been ever increasing worldwide since its outbreak in Wuhan, China. As such, many researchers have sought to predict the dynamics of the virus spread in different parts of the globe. In this paper, a novel systematic platform for prediction of the future number of confirmed cases of COVID-19 is proposed, based on several factors such as transmission rate, temperature, and humidity. The proposed strategy derives systematically a set of appropriate features for training Recurrent Neural Networks (RNN). To that end, the number of confirmed cases (CC) of COVID-19 in three states of India (Maharashtra, Tamil Nadu and Gujarat) is taken as a case study. It has been noted that stationary and nonstationary parts of the features improved the prediction of the stationary and non-stationary trends of the number of confirmed cases, respectively. The new platform has general application and can be used for pandemic time series forecasting. |
| 关键词 | COVID-19 Time series analysis Recurrent neural networks Temperature measurement Systematics Globalization India China Pandemics Predictive models |
| DOI | 10.1109/MCI.2020.3019895 |
| WOS关键词 | COINTEGRATION |
| WOS研究方向 | Computer Science |
| WOS类目 | Computer Science, Artificial Intelligence |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 专题 | 新冠肺炎 循证社会科学证据集成 |
| 作者单位 | 1.Univ Tasmania; 2.Univ Technol Sydney; 3.Thapar Inst Engn & Technol |
| 推荐引用方式 GB/T 7714 | Mousavi, Mohsen,Holloway, Damien,Gandomi, Amir H.,et al. COVID-19 Time Series Forecast Using Transmission Rate and Meteorological Parameters as Features[J]. IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE,2020. |
| APA | Mousavi, Mohsen,Holloway, Damien,Gandomi, Amir H.,&Salgotra, Rohit.(2020).COVID-19 Time Series Forecast Using Transmission Rate and Meteorological Parameters as Features.IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE. |
| MLA | Mousavi, Mohsen,et al."COVID-19 Time Series Forecast Using Transmission Rate and Meteorological Parameters as Features".IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE (2020). |
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| COVID-19 Time Series（1892KB） | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 | |
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