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Predictive Models for Cumulative Confirmed COVID-19 Cases by Day in Southeast Asia 被引量:2

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摘要 Coronavirus disease 2019 outbreak has spread as a pandemic since the end of year 2019.This situation has been causing a lot of problems of human beings such as economic problems,health problems.The forecasting of the number of infectious people is required by the authorities of all countries including Southeast Asian countries to make a decision and control the outbreak.This research is to investigate the suitable forecasting model for the number of infectious people in Southeast Asian countries.A comparison of forecasting models between logistic growth curve which is symmetric and Gompertz growth curve which is asymmetric based on the maximumof Coefficient of Determination and theminimumof RootMean Squared Percentage Error is also proposed.The estimation of parameters of the forecasting models is evaluated by the least square method.In addition,spreading of the outbreak is estimated by the derivative of the number of cumulative cases.The findings show that Gompertz growth curve is a suitable forecasting model for Indonesia,Philippines,andMalaysia and logistic growth curve suits the other countries in South Asia.
出处 《Computer Modeling in Engineering & Sciences》 SCIE EI 2020年第12期927-942,共16页 工程与科学中的计算机建模(英文)
基金 The research was funding by King Mongkut’s University of Technology North Bangkok Contract No.KMUTNB-61-GOV-03-23.
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