According to groundwater level monitoring data of Shuping landslide in the Three Gorges Reservoir area, based on the response relationship between influential factors such as rainfall and reservoir level and the chang...According to groundwater level monitoring data of Shuping landslide in the Three Gorges Reservoir area, based on the response relationship between influential factors such as rainfall and reservoir level and the change of groundwater level, the influential factors of groundwater level were selected. Then the classification and regression tree（CART） model was constructed by the subset and used to predict the groundwater level. Through the verification, the predictive results of the test sample were consistent with the actually measured values, and the mean absolute error and relative error is 0.28 m and 1.15%respectively. To compare the support vector machine（SVM） model constructed using the same set of factors, the mean absolute error and relative error of predicted results is 1.53 m and 6.11% respectively. It is indicated that CART model has not only better fitting and generalization ability, but also strong advantages in the analysis of landslide groundwater dynamic characteristics and the screening of important variables. It is an effective method for prediction of ground water level in landslides.展开更多
In this study,analyses are conducted on the information features of a construction site,a cornfield and subsidence seeper land in a coal mining area with a synthetic aperture radar (SAR) image of medium resolution. Ba...In this study,analyses are conducted on the information features of a construction site,a cornfield and subsidence seeper land in a coal mining area with a synthetic aperture radar (SAR) image of medium resolution. Based on features of land cover of the coal mining area,on texture feature extraction and a selection method of a gray-level co-occurrence matrix (GLCM) of the SAR image,we propose in this study that the optimum window size for computing the GLCM is an appropriate sized window that can effectively distinguish different types of land cover. Next,a band combination was carried out over the text feature images and the band-filtered SAR image to secure a new multi-band image. After the transformation of the new image with principal component analysis,a classification is conducted selectively on three principal component bands with the most information. Finally,through training and experimenting with the samples,a better three-layered BP neural network was established to classify the SAR image. The results show that,assisted by texture information,the neural network classification improved the accuracy of SAR image classification by 14.6%,compared with a classification by maximum likelihood estimation without texture information.展开更多
分析了3层式广域保护系统需要传输的消息种类以及各类消息对通信系统的要求,在此基础上选择了IP over ATM over SDH作为网络类型,以充分利用同步数字体系(SDH)光纤自愈环的低时延和可靠性以及异步传送模式(ATM)的服务质量(QoS)和IP的多...分析了3层式广域保护系统需要传输的消息种类以及各类消息对通信系统的要求,在此基础上选择了IP over ATM over SDH作为网络类型,以充分利用同步数字体系(SDH)光纤自愈环的低时延和可靠性以及异步传送模式(ATM)的服务质量(QoS)和IP的多业务支持;设计了多环网络拓扑并探讨了关键消息传输的通信协议;使用OPNET Modeler对关键信息传输进行了仿真,证实了此通信系统的有效性,仿真结果表明该通信系统可以满足最恶劣情况下的实时性和可靠性要求。展开更多
基金supported by the China Earthquake Administration, Institute of Seismology Foundation (IS201526246)
文摘According to groundwater level monitoring data of Shuping landslide in the Three Gorges Reservoir area, based on the response relationship between influential factors such as rainfall and reservoir level and the change of groundwater level, the influential factors of groundwater level were selected. Then the classification and regression tree（CART） model was constructed by the subset and used to predict the groundwater level. Through the verification, the predictive results of the test sample were consistent with the actually measured values, and the mean absolute error and relative error is 0.28 m and 1.15%respectively. To compare the support vector machine（SVM） model constructed using the same set of factors, the mean absolute error and relative error of predicted results is 1.53 m and 6.11% respectively. It is indicated that CART model has not only better fitting and generalization ability, but also strong advantages in the analysis of landslide groundwater dynamic characteristics and the screening of important variables. It is an effective method for prediction of ground water level in landslides.
基金Projects 40771143 supported by the National Natural Science Foundation of China2007AA12Z162 by the Hi-tech Research and Development Program of China
文摘In this study,analyses are conducted on the information features of a construction site,a cornfield and subsidence seeper land in a coal mining area with a synthetic aperture radar (SAR) image of medium resolution. Based on features of land cover of the coal mining area,on texture feature extraction and a selection method of a gray-level co-occurrence matrix (GLCM) of the SAR image,we propose in this study that the optimum window size for computing the GLCM is an appropriate sized window that can effectively distinguish different types of land cover. Next,a band combination was carried out over the text feature images and the band-filtered SAR image to secure a new multi-band image. After the transformation of the new image with principal component analysis,a classification is conducted selectively on three principal component bands with the most information. Finally,through training and experimenting with the samples,a better three-layered BP neural network was established to classify the SAR image. The results show that,assisted by texture information,the neural network classification improved the accuracy of SAR image classification by 14.6%,compared with a classification by maximum likelihood estimation without texture information.
文摘分析了3层式广域保护系统需要传输的消息种类以及各类消息对通信系统的要求,在此基础上选择了IP over ATM over SDH作为网络类型,以充分利用同步数字体系(SDH)光纤自愈环的低时延和可靠性以及异步传送模式(ATM)的服务质量(QoS)和IP的多业务支持;设计了多环网络拓扑并探讨了关键消息传输的通信协议;使用OPNET Modeler对关键信息传输进行了仿真,证实了此通信系统的有效性,仿真结果表明该通信系统可以满足最恶劣情况下的实时性和可靠性要求。
