目的介绍模拟指标与观测指标之间的距离(distance between indices of simulation and observation,DISO)在传染病预测模型效果评价中的应用,为传染病预测模型评价提供参考。方法以2005—2021年湖北省细菌性痢疾逐月发病率数据为例,分...目的介绍模拟指标与观测指标之间的距离(distance between indices of simulation and observation,DISO)在传染病预测模型效果评价中的应用,为传染病预测模型评价提供参考。方法以2005—2021年湖北省细菌性痢疾逐月发病率数据为例,分别建立季节自回归移动平均模型(seasonal autoregressive integrated moving average model,SARIMA)、指数平滑空间状态模型(exponential smoothing state space model,ETS)、TBATS模型(三角函数季节性、Box-Cox变换、ARMA误差、趋势和季节性成分组合模型)和自回归神经网络模型(neural network autoregression,NNETAR)以及上述模型的组合模型共5种模型,预测2022年1—12月湖北省细菌性痢疾发病率。选择平均绝对误差百分比(mean absolute percentage error,MAPE)、平均绝对误差(meanabsoluteerror,MAE)、均方误差根(rootmeansquareerror,RMSE)、平均误差率(mean error rate,MER)以及R2共5个评价指标计算拟合DISO值、预测DISO值和综合DISO值,利用DISO选择最优模型。结果SARIMA、ETS、TBATS、NNETAR和组合模型拟合的MAPE、MAE、RMSE、MER和R2的模型精度顺位分别为5、5、5、5、4;2、2、3、2、4;4、4、2、4、2;3、2、3、2、2;1、1、1、1、1。模型预测精度顺位存在较大差异。SARIMA、ETS、TBATS、NNETAR和组合模型拟合DISO值依次为1.00、0.68、0.74、0.62和0.00,预测DISO值依次为1.00、0.00、0.01、0.17和0.01,综合DISO值依次为1.41、0.68、0.74、0.65和0.01。拟合精度最高模型为组合模型,预测精度最高模型为ETS,拟合及预测综合精度最高的为组合模型。结论DISO可以用于传染病预测模型效果评价,值得推广应用。展开更多
Inter-area low frequency oscillation in power system is one of the major problems for bulk power transmission through weak tie lines.Use of wide-area signal is more effective than the local area signal in damping out ...Inter-area low frequency oscillation in power system is one of the major problems for bulk power transmission through weak tie lines.Use of wide-area signal is more effective than the local area signal in damping out the inter-area oscillations.Wide area measurement system(WAMS)is convenient to transmit the wide area signal through the communication channel to the remote location.Communication failure is one of the disastrous phenomena in a communication channel.In this paper,a dual input single output(DISO)Hm controller is designed to build the control resiliency by employing two highest observability ranking wide area signals with respect to the critical damping inter-area mode.The proposed controller can provide sufficient damping to the system and also the system remains stabilized if one of the wide-area signals is lost.The time delay is an unwanted phenomenon that degrades the performance of the controllers.The unified Smith predictor approach is used to design a Hm controller to handle the time delay.Kundur's two-area and IEEE-39 bus test systems are considered to verify the effectiveness of the proposed controller.From the simulation results,it is verified that,the proposed controller provides excellent damping performance at normal communication and improves the controller resiliency to counteract the communication failure.展开更多
文摘目的介绍模拟指标与观测指标之间的距离(distance between indices of simulation and observation,DISO)在传染病预测模型效果评价中的应用,为传染病预测模型评价提供参考。方法以2005—2021年湖北省细菌性痢疾逐月发病率数据为例,分别建立季节自回归移动平均模型(seasonal autoregressive integrated moving average model,SARIMA)、指数平滑空间状态模型(exponential smoothing state space model,ETS)、TBATS模型(三角函数季节性、Box-Cox变换、ARMA误差、趋势和季节性成分组合模型)和自回归神经网络模型(neural network autoregression,NNETAR)以及上述模型的组合模型共5种模型,预测2022年1—12月湖北省细菌性痢疾发病率。选择平均绝对误差百分比(mean absolute percentage error,MAPE)、平均绝对误差(meanabsoluteerror,MAE)、均方误差根(rootmeansquareerror,RMSE)、平均误差率(mean error rate,MER)以及R2共5个评价指标计算拟合DISO值、预测DISO值和综合DISO值,利用DISO选择最优模型。结果SARIMA、ETS、TBATS、NNETAR和组合模型拟合的MAPE、MAE、RMSE、MER和R2的模型精度顺位分别为5、5、5、5、4;2、2、3、2、4;4、4、2、4、2;3、2、3、2、2;1、1、1、1、1。模型预测精度顺位存在较大差异。SARIMA、ETS、TBATS、NNETAR和组合模型拟合DISO值依次为1.00、0.68、0.74、0.62和0.00,预测DISO值依次为1.00、0.00、0.01、0.17和0.01,综合DISO值依次为1.41、0.68、0.74、0.65和0.01。拟合精度最高模型为组合模型,预测精度最高模型为ETS,拟合及预测综合精度最高的为组合模型。结论DISO可以用于传染病预测模型效果评价,值得推广应用。
基金support by the Central Power Research Institute,India(CPRI/RD/RSOP/GRANT/2015)
文摘Inter-area low frequency oscillation in power system is one of the major problems for bulk power transmission through weak tie lines.Use of wide-area signal is more effective than the local area signal in damping out the inter-area oscillations.Wide area measurement system(WAMS)is convenient to transmit the wide area signal through the communication channel to the remote location.Communication failure is one of the disastrous phenomena in a communication channel.In this paper,a dual input single output(DISO)Hm controller is designed to build the control resiliency by employing two highest observability ranking wide area signals with respect to the critical damping inter-area mode.The proposed controller can provide sufficient damping to the system and also the system remains stabilized if one of the wide-area signals is lost.The time delay is an unwanted phenomenon that degrades the performance of the controllers.The unified Smith predictor approach is used to design a Hm controller to handle the time delay.Kundur's two-area and IEEE-39 bus test systems are considered to verify the effectiveness of the proposed controller.From the simulation results,it is verified that,the proposed controller provides excellent damping performance at normal communication and improves the controller resiliency to counteract the communication failure.
