Linling Yu|Lingling Zhou|Li Tan|Hongbo Jiang|Ying Wang|Sheng Wei|Shaoping Nie
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
Huazhong University of Science and Technology|Huazhong University of Science and Technology|Huazhong University of Science and Technology|Huazhong University of Science and Technology|Huazhong University of Science and Technology|Huazhong University of Science and Technology|Huazhong University of Science and Technology
outbreaks handfootmouth disease hfmd reported many times asia last decades emerging disease drawn worldwide attention vigilance nowadays prevention control hfmd become imperative issue china early detection response helpful happening using modern information technology epidemicin paper hybrid model combining seasonal autoregressive integrated moving average arima model nonlinear autoregressive neural network narnn proposed predict expected incidence cases december 2012 may 2013 using retrospective observations obtained china information system disease control prevention january 2008 november 2012the bestfitted hybrid model combined seasonal arima formula see text narnn 15 hidden units 5 delays hybrid model makes good forecasting performance estimates expected incidence cases december 2012 may 2013 respectively 96503 187958 413826 185817 406186 616316 obviously increasing trendthe model proposed paper predict incidence trend hfmd effectively could helpful policy makers usefulness expected cases hfmd perform detecting outbreaks providing probability statements also providing decision makers probable trend variability future observations contains historical recent information