title: [Predicting Incidence of Hepatitis E in Chinausing Fuzzy Time Series Based on Fuzzy C-Means Clustering Analysis].
abstract: OBJECTIVE
  To explore the application of fuzzy time series model based on fuzzy c-means clustering in forecasting monthly incidence of Hepatitis E in mainland China.
  
  
  METHODS
  Apredictive model (fuzzy time series method based on fuzzy c-means clustering) was developed using Hepatitis E incidence data in mainland China between January 2004 and July 2014. The incidence datafrom August 2014 to November 2014 were used to test the fitness of the predictive model. The forecasting results were compared with those resulted from traditional fuzzy time series models.
  
  
  RESULTS
  The fuzzy time series model based on fuzzy c-means clustering had 0.001 1 mean squared error (MSE) of fitting and 6.977 5 x 10⁻⁴ MSE of forecasting, compared with 0.0017 and 0.0014 from the traditional forecasting model.
  
  
  CONCLUSIONS
  The results indicate that the fuzzy time series model based on fuzzy c-means clustering has a better performance in forecasting incidence of Hepatitis E.
authors.forename: Yi
authors.initials: Y
authors.lastname: Luo
authors.forename: Tao
authors.initials: T
authors.lastname: Zhang
authors.forename: Xiao-song
authors.initials: XS
authors.lastname: Li
mesh_terms: D002681:China; D016000:Cluster Analysis; D005544:Forecasting; D016751:Hepatitis E / Q000453:epidemiology*; D006801:Humans; D015994:Incidence; D008962:Models, Theoretical