Conference Paper/Proceeding/Abstract 448 views
Modelling and Predicting the Dynamics of Confirmed COVID-19 Cases Based on Climate Data
Contributions to Statistics, Pages: 105 - 115
Swansea University Authors: Yuzhi Cai , Fangzhou Huang
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DOI (Published version): 10.1007/978-3-031-40209-8_8
Abstract
Modelling and Predicting the Dynamics of Confirmed COVID-19 Cases Based on Climate Data
Published in: | Contributions to Statistics |
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ISBN: | 9783031402081 9783031402098 |
ISSN: | 1431-1968 |
Published: |
Cham
Springer Nature Switzerland
2023
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URI: | https://cronfa.swan.ac.uk/Record/cronfa61876 |
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2023-01-27T04:15:55Z |
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title |
Modelling and Predicting the Dynamics of Confirmed COVID-19 Cases Based on Climate Data |
spellingShingle |
Modelling and Predicting the Dynamics of Confirmed COVID-19 Cases Based on Climate Data Yuzhi Cai Fangzhou Huang |
title_short |
Modelling and Predicting the Dynamics of Confirmed COVID-19 Cases Based on Climate Data |
title_full |
Modelling and Predicting the Dynamics of Confirmed COVID-19 Cases Based on Climate Data |
title_fullStr |
Modelling and Predicting the Dynamics of Confirmed COVID-19 Cases Based on Climate Data |
title_full_unstemmed |
Modelling and Predicting the Dynamics of Confirmed COVID-19 Cases Based on Climate Data |
title_sort |
Modelling and Predicting the Dynamics of Confirmed COVID-19 Cases Based on Climate Data |
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Yuzhi Cai Fangzhou Huang |
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Yuzhi Cai Fangzhou Huang Jiao Song |
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Contributions to Statistics |
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105 |
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1431-1968 |
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10.1007/978-3-031-40209-8_8 |
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Springer Nature Switzerland |
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