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https://zone.biblio.laurentian.ca/handle/10219/3569
Titre: | Forecasting COVID-19 with gamma model |
Auteurs: | Tang, Zhenyao |
Mots clés: | Forecasting;forecasting verification;COVID-19;World Health Organization;WHO;gamma distribution;non-linear regression;dashboard prototype;jQuery |
Date publié: | 17-aoû-2020 |
Abstrait: | COVID-19 is a highly contagiously atypical pneumonia attributed to a novel coronavirus. The global economy and people's lives have been tremendously affected by the COVID-19 pandemic since its outbreak in Wuhan, Hubei province, China. In this thesis, a non-linear model based on gamma distribution was built to verify the accuracy of the forecasting of the total confirmed cases of COVID-19 two weeks ahead. The daily growth in cases of COVID-19 for different countries was monitored and compared with the forecasted values. The verification of the performance of the non-linear Gamma distribution model has been verified by the non-linear regression. The data for the 19 countries with the most total confirmed COVID-19 cases as of June 22 was used. The data was sourced from the interactive web-based dashboard developed by the Center for System Science and Engineering (CSSE) at Johns Hopkins University. A web page has been developed to provide predictions generated by our models for individuals and public organizations to forecast the trends of COVID19. |
URI: | https://zone.biblio.laurentian.ca/handle/10219/3569 |
Apparaît dans les collections: | Computational Sciences - Master's theses Master's Theses |
Fichiers dans cet item:
Fichier | Description | Taille | Format | |
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Thesis_ZhenyaoTang_0375307.pdf | 2.47 MB | Adobe PDF | Parcourir/Ouvrir |
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