2篇
您的检索式：作者名="NI WenChen"
|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | Micromechanical characteristics of the asphalt mixture in bending condition显示文摘The characteristics of asphalt mixtures are associated with the key features of the mixed material when it is not damaged.Two-dimensional(2D) microstructure images of asphalt mixture bending beam specimen were captured by a CCD camera.After image processing,such as noise elimination,boundary identification,image binarization and vectorization,the images were imported into finite element(FE) software in order to set up the micromechanical finite element(FE) model.The simulation results show that the displacement contours spectrum is not a smooth curve since the mixed material is heterogeneous.Also,the largest strain value exists at the bottom of the specimen between two coarse aggregates,and it is the point where the fracture starts.The stress values of aggregates are larger than those of the asphalt matrix.Different from the strain of asphalt matrix,the strain of aggregates is close to zero because the aggregates have higher capability to resist self-deformation.The difference in deformation between aggregate and asphalt matrix can lead to an interface crack as a final result.All these results can be improved by three-point bending test of asphalt mixture beam. | CUI YaNan XING YongMing NI WenChen | 2013 | Science China(Technological Sciences)2013，56，2： | 1 |
| 2 | Predicting the severity of traffic accidents on mountain freeways with dynamic traffic and weather data显示文摘Traffic accident severity prediction is essential for dynamic traffic safety management.To explore the factors influencing the severity of traffic accidents on mountain freeways and to predict the severity of traffic accidents,four models based on machine learning algorithms are constructed using support vector machine(SVM),decision tree classifier(DTC),Ada_SVM and Ada_DTC.In addition,random forest(RF)is used to calculate the importance degree of variables and the accident severity influences with high importance levels form the RF dataset.The results show that rainfall intensity,collision type,number of vehicles involved in the accident and toad section type are important variables influencing accident severity.The RF feature selection method improves the classification performance of four machine leaming algorithms,resulting in a 9.3%,5.5%,7.2% and 3.6% improvement in prediction accuracy for SVM,DTC,Ada_SVM and Ada_DTC,respectively.The combination of the Ada_SVM integrated algorithm and RF feature selection method has the best prediction performance,and it achieves 78.9% and 88.4% prediction precision and accuracy,respectively. | Juan Li Fengxiang Guo Yanning Zhou Wenchen Yang Dingan Ni | 2023 | Transportation Safety and Environment2023，5，4： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员