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• W4283397497 abstract "The Corona virus pandemic is the most tragic virus outbreak in more than a century. Corona has globally already taken the lives of four million people, across all continents. The virus has the potential to become very catastrophic, if a significant part of the world population does not have any form of immunity against it. In this project, the aim is to make forecasts on the number of daily infections in the Netherlands. Seven different models were implemented to forecast the number of infected people in a three-month time period. The sequential CNN model outperformed all other models substantially. The capabilities of CNN models in time series forecasting can be very encouraging in conducting more research on time series data with convolutional neural networks." @default.
• W4283397497 created "2022-06-25" @default.
• W4283397497 creator A5072243254 @default.
• W4283397497 date "2022-10-26" @default.
• W4283397497 modified "2023-09-25" @default.
• W4283397497 title "Time Series Forecasting on COVID-19 Data and Its Relevance to International Health Security" @default.
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• W4283397497 doi "https://doi.org/10.5772/intechopen.104920" @default.
• W4283397497 hasPublicationYear "2022" @default.
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