APPLICATIONS OF ARIMA MODEL ON PREDICTIVE WORK LOAD OF IN-PATIENT DEPARTMENT
Liu Li · Xiandai yufang yixue · 2009
[Objective] To establish a model of multiple seasonal autoregressive integrated moving average (ARIMA) (p, d, q) (P, D, Q) s on time-serial data, and to predict for the seasonal time series. [Methods] Statistic of Box- Ljung was used to evaluate the degree of fitness of ARIMA model, and the average relative errors of predict were used to be indexes to evaluate the predictive effect. [Results] Model of multiple seasonal ARIMA (0, 1, 1) (0, 1, 2) s was established for the time series analyzed with an average relative error of 6.50%. [Conclusion] The model of ARIMA can be used to forecast the number of inpatients, and our study indicated ARIMA was a prediction model with high precision.