title: Application of a hybrid method combining grey model and back propagation artificial neural networks to forecast hepatitis B in china.
abstract: Accurate incidence forecasting of infectious disease provides potentially valuable insights in its own right. It is critical for early prevention and may contribute to health services management and syndrome surveillance. This study investigates the use of a hybrid algorithm combining grey model (GM) and back propagation artificial neural networks (BP-ANN) to forecast hepatitis B in China based on the yearly numbers of hepatitis B and to evaluate the method's feasibility. The results showed that the proposal method has advantages over GM (1, 1) and GM (2, 1) in all the evaluation indexes.
authors: School of Preclinical Medicine, Guangxi Medical University, No. 22, Shuangyong Road, Nanning, Guangxi 530021, China.
authors: Ruijing
authors: R
authors: Gan
authors: School of Preclinical Medicine, Guangxi Medical University, No. 22, Shuangyong Road, Nanning, Guangxi 530021, China.
authors: Xiaojun
authors: X
authors: Chen
authors: School of Preclinical Medicine, Guangxi Medical University, No. 22, Shuangyong Road, Nanning, Guangxi 530021, China.
authors: Yu
authors: Y
authors: Yan
authors: School of Preclinical Medicine, Guangxi Medical University, No. 22, Shuangyong Road, Nanning, Guangxi 530021, China.
authors: Daizheng
authors: D
authors: Huang
mesh_terms: D000465:Algorithms; D002681:China; D003140:Communicable Disease Control / Q000379:methods; D006509:Hepatitis B / Q000175:diagnosis* / Q000453:epidemiology*; D006801:Humans; D055552:Infectious Disease Medicine; D008490:Medical Informatics; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D011237:Predictive Value of Tests; D012984:Software