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

Title
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
Authors
Keywords
Hand, foot and mouth disease, Forecasting, Artificial neural networks, China, Epidemiology, Disease informatics, Infectious disease control, Neural networks
Journal
PLoS One
Volume 9, Issue 6, Pages e98241
Publisher
Public Library of Science (PLoS)
Online
2014-06-04
DOI
10.1371/journal.pone.0098241

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