Application of a new hybrid model with seasonal auto-regressive integrated moving average (ARIMA) and nonlinear auto-regressive neural network (NARNN) in forecasting incidence cases of HFMD in Shenzhen, China.
Yu, Lijing
Application of a new hybrid model with seasonal auto-regressive integrated moving average (ARIMA) and nonlinear auto-regressive neural network (NARNN) in forecasting incidence cases of HFMD in Shenzhen, China. [electronic resource] - PloS one 2014 - e98241 p. digital
Publication Type: Journal Article; Research Support, Non-U.S. Gov't
1932-6203
10.1371/journal.pone.0098241 doi
Child, Preschool
China--epidemiology
Demography
Epidemics
Female
Forecasting
Hand, Foot and Mouth Disease--epidemiology
Humans
Incidence
Infant
Infant, Newborn
Male
Models, Statistical
Neural Networks, Computer
Nonlinear Dynamics
Regression Analysis
Reproducibility of Results
Seasons
Time Factors
Application of a new hybrid model with seasonal auto-regressive integrated moving average (ARIMA) and nonlinear auto-regressive neural network (NARNN) in forecasting incidence cases of HFMD in Shenzhen, China. [electronic resource] - PloS one 2014 - e98241 p. digital
Publication Type: Journal Article; Research Support, Non-U.S. Gov't
1932-6203
10.1371/journal.pone.0098241 doi
Child, Preschool
China--epidemiology
Demography
Epidemics
Female
Forecasting
Hand, Foot and Mouth Disease--epidemiology
Humans
Incidence
Infant
Infant, Newborn
Male
Models, Statistical
Neural Networks, Computer
Nonlinear Dynamics
Regression Analysis
Reproducibility of Results
Seasons
Time Factors