The 3-hour-interval prediction of ground-level temperature from +00 h out to +45 h in South Korea (38 stations) is performed using the DLM (dynamic linear model) in order to eliminate the systematic error of numerical...The 3-hour-interval prediction of ground-level temperature from +00 h out to +45 h in South Korea (38 stations) is performed using the DLM (dynamic linear model) in order to eliminate the systematic error of numerical model forecasts. Numerical model forecasts and observations are used as input values of the DLM. According to the comparison of the DLM forecasts to the KFM (Kalman filter model) forecasts with RMSE and bias, the DLM is useful to improve the accuracy of prediction.展开更多
This paper presents a study on the statistical forecasts of typhoon tracks. Numerical models have their own systematic errors, like a bias. In order to improve the accuracy of track forecasting, a statistical model ca...This paper presents a study on the statistical forecasts of typhoon tracks. Numerical models have their own systematic errors, like a bias. In order to improve the accuracy of track forecasting, a statistical model called DLM (dynamic linear model) is applied to remove the systematic error. In the analysis of typhoons occurring over the western North Pacific in 1997 and 2000, DLM is useful as an adaptive model for the prediction of typhoon tracks.展开更多
Dear Editor,Aiming at the consensus tracking problem of a class of unknown heterogeneous nonlinear multiagent systems(MASs)with input constraints,a novel data-driven iterative learning consensus control(ILCC)protocol ...Dear Editor,Aiming at the consensus tracking problem of a class of unknown heterogeneous nonlinear multiagent systems(MASs)with input constraints,a novel data-driven iterative learning consensus control(ILCC)protocol based on zeroing neural networks(ZNNs)is proposed.First,a dynamic linearization data model(DLDM)is acquired via dynamic linearization technology(DLT).展开更多
This article presented a new data fusion approach for reasonably predicting dynamic serviceability reliability of the long-span bridge girder.Firstly,multivariate Bayesian dynamic linear model(MBDLM)considering dynami...This article presented a new data fusion approach for reasonably predicting dynamic serviceability reliability of the long-span bridge girder.Firstly,multivariate Bayesian dynamic linear model(MBDLM)considering dynamic correlation among the multiple variables is provided to predict dynamic extreme deflections;secondly,with the proposed MBDLM,the dynamic correlation coefficients between any two performance functions can be predicted;finally,based on MBDLM and Gaussian copula technique,a new data fusion method is given to predict the serviceability reliability of the long-span bridge girder,and the monitoring extreme deflection data from an actual bridge is provided to illustrated the feasibility and application of the proposed method.展开更多
Spatio-temporal data analysis is an emerging research area due to the development and application ofnovel computational techniques allowing for the analysis of large spatiotemporal databases.We consider a general clas...Spatio-temporal data analysis is an emerging research area due to the development and application ofnovel computational techniques allowing for the analysis of large spatiotemporal databases.We consider a general class of spatio-temporal linear models,where the number of structural breaks can tend to infinity.A procedure for simultaneously detecting all the change points is developed rigorously via the construction of adaptive group lasso penalty.Consistency of the multiple change point estimation is established under mild technical conditions even when the true number of change points sn diverges with the series length n.The adaptive group lasso can be substituted by the group lasso and other non-convex group selection penalty functions such as group SCAD or group MCP.The simulation studies demonstrate that our procedure is stable and accurate.Two empirical examples from property market,including the housing transaction price in Baton Rouge and the commodity apartment price in Hong Kong,are analyzed to fully illustrate the proposed methodology.展开更多
We propose a new functional single index model, which called dynamic single-index model for functional data, or DSIM, to efficiently perform non-linear and dynamic relationships between functional predictor and functi...We propose a new functional single index model, which called dynamic single-index model for functional data, or DSIM, to efficiently perform non-linear and dynamic relationships between functional predictor and functional response. The proposed model naturally allows for some curvature not captured by the ordinary functional linear model. By using the proposed two-step estimating algorithm, we develop the estimates for both the link function and the regression coefficient function, and then provide predictions of new response trajectories. Besides the asymptotic properties for the estimates of the unknown functions, we also establish the consistency of the predictions of new response trajectories under mild conditions. Finally, we show through extensive simulation studies and a real data example that the proposed DSIM can highly outperform existed functional regression methods in most settings.展开更多
The capture control of test mass by means of the electrostatic suspensions is crucial for drag-free spacecraft.The test mass must be released to the cage center of the inertial sensor accurately and quickly.This paper...The capture control of test mass by means of the electrostatic suspensions is crucial for drag-free spacecraft.The test mass must be released to the cage center of the inertial sensor accurately and quickly.This paper proposes a minimum-time capture control method for the test mass release phase of drag-free spacecraft.An analytical solution of optimal control is derived based on Pontryagin’s minimum principle and the linearized dynamics model of the test mass during the release phase.The parameters of the analytical solution are initially guessed with an approximate linear solution of the test mass dynamics model and are slightly modified by using differential correction.Compared with the exact numerical solution by the hp-adaptive pseudospectral method,the analytical solution is proved to be minimum-time.Numerical simulation shows that the proposed control method quickly captures the test mass to the cage center of the inertial sensor.The capture time to stabilization is only half that of the traditional controller.展开更多
文摘The 3-hour-interval prediction of ground-level temperature from +00 h out to +45 h in South Korea (38 stations) is performed using the DLM (dynamic linear model) in order to eliminate the systematic error of numerical model forecasts. Numerical model forecasts and observations are used as input values of the DLM. According to the comparison of the DLM forecasts to the KFM (Kalman filter model) forecasts with RMSE and bias, the DLM is useful to improve the accuracy of prediction.
基金the project"A study on improving forecast skill using a su-percomputer"of Meteorological Research Institute,KMA,2001.
文摘This paper presents a study on the statistical forecasts of typhoon tracks. Numerical models have their own systematic errors, like a bias. In order to improve the accuracy of track forecasting, a statistical model called DLM (dynamic linear model) is applied to remove the systematic error. In the analysis of typhoons occurring over the western North Pacific in 1997 and 2000, DLM is useful as an adaptive model for the prediction of typhoon tracks.
基金supported by the National Nature Science Foundation of China(U21A20166)the Science and Technology Development Foundation of Jilin Province(20230508095RC)+2 种基金the Major Science and Technology Projects of Jilin Province and Changchun City(20220301033GX)the Development and Reform Commission Foundation of Jilin Province(2023C034-3)the Interdisciplinary Integration and Innovation Project of JLU(JLUXKJC2020202).
文摘Dear Editor,Aiming at the consensus tracking problem of a class of unknown heterogeneous nonlinear multiagent systems(MASs)with input constraints,a novel data-driven iterative learning consensus control(ILCC)protocol based on zeroing neural networks(ZNNs)is proposed.First,a dynamic linearization data model(DLDM)is acquired via dynamic linearization technology(DLT).
基金This work was supported by Natural Science Foundation of Gansu Province of China(20JR10RA625,20JR10RA623)National Key Research and Development Project of China(Project No.2019YFC1511005)+1 种基金Fundamental Research Funds for the Central Universities(Grant No.lzujbky-2020-55)National Natural Science Foundation of China(Grant No.51608243).
文摘This article presented a new data fusion approach for reasonably predicting dynamic serviceability reliability of the long-span bridge girder.Firstly,multivariate Bayesian dynamic linear model(MBDLM)considering dynamic correlation among the multiple variables is provided to predict dynamic extreme deflections;secondly,with the proposed MBDLM,the dynamic correlation coefficients between any two performance functions can be predicted;finally,based on MBDLM and Gaussian copula technique,a new data fusion method is given to predict the serviceability reliability of the long-span bridge girder,and the monitoring extreme deflection data from an actual bridge is provided to illustrated the feasibility and application of the proposed method.
基金National Natural Science Foundation of China(General Program,No.11571337,71873128,Key Program,No.71631006)Natural Sciences and Engineering Research Council of Canada(Grant No.RGPIN-2017-05720)。
文摘Spatio-temporal data analysis is an emerging research area due to the development and application ofnovel computational techniques allowing for the analysis of large spatiotemporal databases.We consider a general class of spatio-temporal linear models,where the number of structural breaks can tend to infinity.A procedure for simultaneously detecting all the change points is developed rigorously via the construction of adaptive group lasso penalty.Consistency of the multiple change point estimation is established under mild technical conditions even when the true number of change points sn diverges with the series length n.The adaptive group lasso can be substituted by the group lasso and other non-convex group selection penalty functions such as group SCAD or group MCP.The simulation studies demonstrate that our procedure is stable and accurate.Two empirical examples from property market,including the housing transaction price in Baton Rouge and the commodity apartment price in Hong Kong,are analyzed to fully illustrate the proposed methodology.
基金supported by National Natural Science Foundation of China (Grant No. 11271080)
文摘We propose a new functional single index model, which called dynamic single-index model for functional data, or DSIM, to efficiently perform non-linear and dynamic relationships between functional predictor and functional response. The proposed model naturally allows for some curvature not captured by the ordinary functional linear model. By using the proposed two-step estimating algorithm, we develop the estimates for both the link function and the regression coefficient function, and then provide predictions of new response trajectories. Besides the asymptotic properties for the estimates of the unknown functions, we also establish the consistency of the predictions of new response trajectories under mild conditions. Finally, we show through extensive simulation studies and a real data example that the proposed DSIM can highly outperform existed functional regression methods in most settings.
基金supported by Guangdong Major Project of Basic and Applied Basic Research(grant no.2019B030302001)National Key Research and Development Program(2022YFC2204200)+1 种基金Beijing Nova Program(Z211100002121137)Beijing Natural Science Foundation(1222018).
文摘The capture control of test mass by means of the electrostatic suspensions is crucial for drag-free spacecraft.The test mass must be released to the cage center of the inertial sensor accurately and quickly.This paper proposes a minimum-time capture control method for the test mass release phase of drag-free spacecraft.An analytical solution of optimal control is derived based on Pontryagin’s minimum principle and the linearized dynamics model of the test mass during the release phase.The parameters of the analytical solution are initially guessed with an approximate linear solution of the test mass dynamics model and are slightly modified by using differential correction.Compared with the exact numerical solution by the hp-adaptive pseudospectral method,the analytical solution is proved to be minimum-time.Numerical simulation shows that the proposed control method quickly captures the test mass to the cage center of the inertial sensor.The capture time to stabilization is only half that of the traditional controller.
