Application of Bayesian-regularization BP neural network in the prediction of hospital beds

Objective To explore the application of Bayesian-regularization BP neural network for predicting hospital beds. Methods According to the data of hospital beds from 1990 to 2006,Bayesian-regularization BP neural network was established.The forecast results were compared with exponential smoothing and autoregressive model. Results The relative errors of results with the three methods were 0.58%,3.62% and 1.48% in forecasting hospital beds,respectively.The forecasting result with Bayesian-regularization BP neural network was more precise and effective than that with traditional prediction methods. Conclusion Bayesian-regularization BP neural network predictive model can be used to predict hospital beds.