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The 3-Hour-Interval Prediction of Ground-Level Temperature in South Korea Using Dynamic Linear Models 被引量:3
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作者 Keon-Tae SOHN Deuk-KyunRHA Young-KyungSEO 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2003年第4期575-582,共8页
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
关键词 temperature forecasting systematic error dynamic linear model
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Prediction of Typhoon Tracks Using Dynamic Linear Models
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作者 Keon-Tae SOHN H.Joe KWON Ae-Sook SUH 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2003年第3期379-384,共6页
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
关键词 typhoon track forecast systematic error dynamic linear model
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Dynamic single-index model for functional data 被引量:2
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作者 MA HaiQiang BAI Yang ZHU ZhongYi 《Science China Mathematics》 SCIE CSCD 2016年第12期2561-2584,共24页
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
关键词 functional data analysis dynamic single-index model local linear smoothing prediction
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Data Fusion about Serviceability Reliability Prediction for the Long-Span Bridge Girder Based on MBDLM and Gaussian Copula Technique
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作者 Xueping Fan Guanghong Yang +2 位作者 Zhipeng Shang Xiaoxiong Zhao Yuefei Liu 《Structural Durability & Health Monitoring》 EI 2021年第1期69-83,共15页
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
关键词 dynamic extreme deflection data serviceability reliability prediction structural health monitoring multivariate Bayesian dynamic linear models Gaussian copula technique
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