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Updated: Apr 15, 2026

Modeling Hepatitis B Virus Infection in Non-Hepatic 293T-NE-3NRs Cells
Published on: June 5, 2020
Application of a hybrid method combining grey model and back propagation artificial neural networks to forecast
Ruijing Gan1, Xiaojun Chen1, Yu Yan1
1School of Preclinical Medicine, Guangxi Medical University, No. 22, Shuangyong Road, Nanning, Guangxi 530021, 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.
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