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目的基于时间序列分析预测血液供应量。方法以北京市红十字血液中心的10年血液供应量为基础,应用SPSS统计软件,采用时间序列分析方法,寻找合适的预测供血量的分析方法和优化模型参数。结果时间序列分析中的自回归滑动平均混合模型(ARIMA)比较适合进行血液供应量的预测,模型参数优化结果 ARIMA(1.1.1)具有较好的拟合效果。拟合值与观察值吻合程度较高。结论可应用时间序列分析方法中的ARIMA对血液供应量进行预测,对于策略的制定、科学管理和理性决策有一定的帮助。
Objective To predict the blood supply based on time series analysis. Methods Based on the 10-year blood supply of Beijing Red Cross Blood Center, we applied SPSS statistical software and time series analysis method to find out the appropriate blood supply analysis methods and optimize the model parameters. Results The autoregressive moving average mixed model (ARIMA) in time series analysis is more suitable for predicting the blood supply. ARIMA (1.1.1), which is the optimal result of model parameters, has a good fitting effect. The fitted value is in good agreement with the observed value. Conclusions ARIMA, a time series analysis method, can be used to predict the blood supply, which is helpful for the formulation of strategies, scientific management and rational decision making.