@Article{cmes.2020.012323,
AUTHOR = {Yupaporn Areepong, Rapin Sunthornwat},
TITLE = {Predictive Models for Cumulative Confirmed COVID-19 Cases by Day in Southeast Asia},
JOURNAL = {Computer Modeling in Engineering \& Sciences},
VOLUME = {125},
YEAR = {2020},
NUMBER = {3},
PAGES = {927--942},
URL = {http://www.techscience.com/CMES/v125n3/40804},
ISSN = {1526-1506},
ABSTRACT = {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 maximum of Coefficent of Determination and the minimum of Root Mean 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, and Malaysia and logistic growth curve suits the other
countries in South Asia.

},
DOI = {10.32604/cmes.2020.012323}
}