Forecast of Cerebral Infraction Incidence Rate Based on BP Neural Network and ARIMA Combined Model

Objective Forecast and analysis of cerebral infraction incidence rate are the basis and key work of cerebral infraction prevention and control. At present, forecast of cerebral infraction incidence rate is mainly based on traditional research approach or single artificial neural network technology. Recent study results show that combined forecast model approach enjoys more precise forecast than monomial forecast approach. Methods The paper proposes a new forecast approach based on BP neural network and ARIMA combined mode and makes comprehensive analysis and forecast of the changing trend of cerebral infraction incidence rate in Haixizhou region, Qinghai province of China. Results Forecast results indicate that this approach is more precise in terms of monomial forecast method. Conclusion The combined model is feasible and effective in the forecast of cerebral infraction incidence rate.