Damage detection in structures is performed via vibra-tion based structural identification. Modal information, such as fre-quencies and mode shapes, are widely used for structural dama-ge detection to indicate the hea...Damage detection in structures is performed via vibra-tion based structural identification. Modal information, such as fre-quencies and mode shapes, are widely used for structural dama-ge detection to indicate the health conditions of civil structures.The deep learning algorithm that works on a multiple layer neuralnetwork model termed as deep autoencoder is proposed to learnthe relationship between the modal information and structural stiff-ness parameters. This is achieved via dimension reduction of themodal information feature and a non-linear regression against thestructural stiffness parameters. Numerical tests on a symmetri-cal steel frame model are conducted to generate the data for thetraining and validation, and to demonstrate the efficiency of theproposed approach for vibration based structural damage detec-tion.展开更多
The change processes and trends of shoreline and tidal flat forced by human activities are essential issues for the sustainability of coastal area,which is also of great significance for understanding coastal ecologic...The change processes and trends of shoreline and tidal flat forced by human activities are essential issues for the sustainability of coastal area,which is also of great significance for understanding coastal ecological environment changes and even global changes.Based on field measurements,combined with Linear Regression(LR)model and Inverse Distance Weighing(IDW)method,this paper presents detailed analysis on the change history and trend of the shoreline and tidal flat in Bohai Bay.The shoreline faces a high erosion chance under the action of natural factors,while the tidal flat faces a different erosion and deposition patterns in Bohai Bay due to the impact of human activities.The implication of change rule for ecological protection and recovery is also discussed.Measures should be taken to protect the coastal ecological environment.The models used in this paper show a high correlation coefficient between observed and modeling data,which means that this method can be used to predict the changing trend of shoreline and tidal flat.The research results of present study can provide scientific supports for future coastal protection and management.展开更多
Unusually severe weather is occurring more frequently due to global climate change. Heat waves, rainstorms, snowstorms, and droughts are becoming increasingly common all over the world, threatening human lives and pro...Unusually severe weather is occurring more frequently due to global climate change. Heat waves, rainstorms, snowstorms, and droughts are becoming increasingly common all over the world, threatening human lives and property. Both temperature and precipitation are representative variables usually used to directly reflect and forecast the influences of climate change. In this study, daily data （from 1953 to 1995） and monthly data （from 1950 to 2010） of temperature and precipitation in five regions of the Amur River were examined. The significance of changes in temperature and precipitation was tested using the Mann-Kendall test method. The amplitudes were computed using the linear least-squares regression model, and the extreme temperature and precipitation were analyzed using hydrological statistical methods. The results show the following： the mean annual temperature increased significantly from 1950 to 2010 in the five regions, mainly due to the warming in spring and winter; the annual precipitation changed significantly from 1950 to 2010 only in the lower mainstream of the Amur River; the frequency of extremely low temperature events decreased from 1953 to 1995 in the mainstream of the Amur River; the frequency of high temperature events increased from 1953 to 1995 in the mainstream of the Amur River; and the frequency of extreme precipitation events did not change significantly from 1953 to 1995 in the mainstream of the Amur River. This study provides a valuable theoretical basis for settling disputes between China and Russia on sustainable development and utilization of water resources of the Amur River.展开更多
The paper investigates the sequential observations’ variance change in linear regression model. The procedure is based on a detection function constructed by residual squares of CUSUM and a boundary function which is...The paper investigates the sequential observations’ variance change in linear regression model. The procedure is based on a detection function constructed by residual squares of CUSUM and a boundary function which is designed so that the test has a small probability of false alarm and asymptotic power one. Simulation results show our monitoring procedure performs well when variance change occurs shortly after the monitoring time. The method is still feasible for regression coefficients change or both variance and regression coefficients change problem.展开更多
In this paper we provide a method to test the existence of the change points in the nonparametric regression function of partially linear models with conditional heteroscedastic variance. We propose the test statistic...In this paper we provide a method to test the existence of the change points in the nonparametric regression function of partially linear models with conditional heteroscedastic variance. We propose the test statistic and establish its asymptotic properties under some regular conditions. Some simulation studies are given to investigate the performance of the proposed method in finite samples. Finally, the proposed method is applied to a real data for illustration.展开更多
文摘Damage detection in structures is performed via vibra-tion based structural identification. Modal information, such as fre-quencies and mode shapes, are widely used for structural dama-ge detection to indicate the health conditions of civil structures.The deep learning algorithm that works on a multiple layer neuralnetwork model termed as deep autoencoder is proposed to learnthe relationship between the modal information and structural stiff-ness parameters. This is achieved via dimension reduction of themodal information feature and a non-linear regression against thestructural stiffness parameters. Numerical tests on a symmetri-cal steel frame model are conducted to generate the data for thetraining and validation, and to demonstrate the efficiency of theproposed approach for vibration based structural damage detec-tion.
基金supported by the National Natural Science Foundation of China (41602205, 42293261)the China Geological Survey Program (DD20189506, DD20211301)+2 种基金the Special Investigation Project on Science and Technology Basic Resources of the Ministry of Science and Technology (2021FY101003)the Central Guidance for Local Scientific and Technological Development Fund of 2023the Project of Hebei University of Environmental Engineering (GCY202301)
文摘The change processes and trends of shoreline and tidal flat forced by human activities are essential issues for the sustainability of coastal area,which is also of great significance for understanding coastal ecological environment changes and even global changes.Based on field measurements,combined with Linear Regression(LR)model and Inverse Distance Weighing(IDW)method,this paper presents detailed analysis on the change history and trend of the shoreline and tidal flat in Bohai Bay.The shoreline faces a high erosion chance under the action of natural factors,while the tidal flat faces a different erosion and deposition patterns in Bohai Bay due to the impact of human activities.The implication of change rule for ecological protection and recovery is also discussed.Measures should be taken to protect the coastal ecological environment.The models used in this paper show a high correlation coefficient between observed and modeling data,which means that this method can be used to predict the changing trend of shoreline and tidal flat.The research results of present study can provide scientific supports for future coastal protection and management.
基金supported by the Innovative Project of Scientific Research for Postgraduates in Ordinary Universities in Jiangsu Province (Grant No. CX09B_161Z)the Cultivation Project for Excellent Doctoral Dissertations in Hohai University+1 种基金the Fundamental Research Funds for the Central Universities (Grant No.2010B18714)Special Funds for Scientific Research on Public Causes of the Ministry of Water Resources of China (Grant No. 201001052)
文摘Unusually severe weather is occurring more frequently due to global climate change. Heat waves, rainstorms, snowstorms, and droughts are becoming increasingly common all over the world, threatening human lives and property. Both temperature and precipitation are representative variables usually used to directly reflect and forecast the influences of climate change. In this study, daily data （from 1953 to 1995） and monthly data （from 1950 to 2010） of temperature and precipitation in five regions of the Amur River were examined. The significance of changes in temperature and precipitation was tested using the Mann-Kendall test method. The amplitudes were computed using the linear least-squares regression model, and the extreme temperature and precipitation were analyzed using hydrological statistical methods. The results show the following： the mean annual temperature increased significantly from 1950 to 2010 in the five regions, mainly due to the warming in spring and winter; the annual precipitation changed significantly from 1950 to 2010 only in the lower mainstream of the Amur River; the frequency of extremely low temperature events decreased from 1953 to 1995 in the mainstream of the Amur River; the frequency of high temperature events increased from 1953 to 1995 in the mainstream of the Amur River; and the frequency of extreme precipitation events did not change significantly from 1953 to 1995 in the mainstream of the Amur River. This study provides a valuable theoretical basis for settling disputes between China and Russia on sustainable development and utilization of water resources of the Amur River.
基金Supported by the National Natural Science Foundation of China (Grant Nos.60972150 10926197)the Scienceand Technology Innovation Foundation of Northwestern Polytechnical University (Grant No.2007KJ01033)
文摘The paper investigates the sequential observations’ variance change in linear regression model. The procedure is based on a detection function constructed by residual squares of CUSUM and a boundary function which is designed so that the test has a small probability of false alarm and asymptotic power one. Simulation results show our monitoring procedure performs well when variance change occurs shortly after the monitoring time. The method is still feasible for regression coefficients change or both variance and regression coefficients change problem.
基金Supported by the National Natural Science Foundation of China(No.11271080)
文摘In this paper we provide a method to test the existence of the change points in the nonparametric regression function of partially linear models with conditional heteroscedastic variance. We propose the test statistic and establish its asymptotic properties under some regular conditions. Some simulation studies are given to investigate the performance of the proposed method in finite samples. Finally, the proposed method is applied to a real data for illustration.
