目的构建某精神专科医院急诊量预测模型,分析急诊科就诊人次的变化规律,为精神科急诊服务资源的优化配置提供参考。方法从某精神专科医院信息系统提取2018—2023年急诊患者就诊时间等数据。其中,2018—2022年月度急诊人次(急诊量)用于...目的构建某精神专科医院急诊量预测模型,分析急诊科就诊人次的变化规律,为精神科急诊服务资源的优化配置提供参考。方法从某精神专科医院信息系统提取2018—2023年急诊患者就诊时间等数据。其中,2018—2022年月度急诊人次(急诊量)用于构建自回归积分滑动平均模型(autoregressive integrated moving average model,ARIMA),2023年月度急诊量用于验证该模型的预测效果。结果经模型构建和筛选,确定季节型ARIMA(0,1,0)(1,1,1)^(12)为最优模型,该模型的预测值与实际值吻合性较好,平均相对误差波动在1.6%~26.8%,平均绝对误差波动在9~159人次。结论季节型ARIMA模型能够较准确地预测某精神专科医院急诊量,可为该院人力资源配置及应急调度提供参考,但该预测模型适用于短期预测,如需长期预测,还应不断进行数据拟合,以确保预测的有效性。展开更多
Elastic reverse-time migration can effectively deal with multicomponent seismic data in which the imaging condition based on energy norm can extract the scalar-imaging result from multicomponent data.However,the energ...Elastic reverse-time migration can effectively deal with multicomponent seismic data in which the imaging condition based on energy norm can extract the scalar-imaging result from multicomponent data.However,the energy cross-correlation imaging condition characterized by particle velocity and stress suffers from the problem of overdependence on the background elastic parameters.Therefore,we characterize the elastic-wave energy using the energy-flow vector,which is equal to the energy density,without background elastic parameters.According to the source and receiver wave fields,we propose an imaging energyflow vector and an elastic-wave energy imaging condition.Under the assumption of a planewave solution,the backscattering suppression is verified.The numerical simulations show that the elastic-energy imaging condition can obtain the energy image without backscattering.Compared with the cross-correlation imaging conditions in a vector-based wave field,the proposed imaging condition can eliminate the dependence on the background elastic parameters and effectively process seabed multicomponent data,which are conducive to further providing an interpretation of marine geological structures.展开更多
文摘目的构建某精神专科医院急诊量预测模型,分析急诊科就诊人次的变化规律,为精神科急诊服务资源的优化配置提供参考。方法从某精神专科医院信息系统提取2018—2023年急诊患者就诊时间等数据。其中,2018—2022年月度急诊人次(急诊量)用于构建自回归积分滑动平均模型(autoregressive integrated moving average model,ARIMA),2023年月度急诊量用于验证该模型的预测效果。结果经模型构建和筛选,确定季节型ARIMA(0,1,0)(1,1,1)^(12)为最优模型,该模型的预测值与实际值吻合性较好,平均相对误差波动在1.6%~26.8%,平均绝对误差波动在9~159人次。结论季节型ARIMA模型能够较准确地预测某精神专科医院急诊量,可为该院人力资源配置及应急调度提供参考,但该预测模型适用于短期预测,如需长期预测,还应不断进行数据拟合,以确保预测的有效性。
基金supported by the National Nature Science Foundation of China(No.61801275)Shangdong Provincial Natural Science Foundation(No.ZR2018BF002)+2 种基金China Postdoctoral Science Foundation(No.2017M622242)Basic Research Projects of Science,Education and Industry Integration Pilot Project of Qilu University of Technology(2022PX082)Qingdao Applied Research Projects.
文摘Elastic reverse-time migration can effectively deal with multicomponent seismic data in which the imaging condition based on energy norm can extract the scalar-imaging result from multicomponent data.However,the energy cross-correlation imaging condition characterized by particle velocity and stress suffers from the problem of overdependence on the background elastic parameters.Therefore,we characterize the elastic-wave energy using the energy-flow vector,which is equal to the energy density,without background elastic parameters.According to the source and receiver wave fields,we propose an imaging energyflow vector and an elastic-wave energy imaging condition.Under the assumption of a planewave solution,the backscattering suppression is verified.The numerical simulations show that the elastic-energy imaging condition can obtain the energy image without backscattering.Compared with the cross-correlation imaging conditions in a vector-based wave field,the proposed imaging condition can eliminate the dependence on the background elastic parameters and effectively process seabed multicomponent data,which are conducive to further providing an interpretation of marine geological structures.
