The accurate estimation of road traffic states can provide decision making for travelers and traffic managers. In this work,an algorithm based on kernel-k nearest neighbor(KNN) matching of road traffic spatial charact...The accurate estimation of road traffic states can provide decision making for travelers and traffic managers. In this work,an algorithm based on kernel-k nearest neighbor(KNN) matching of road traffic spatial characteristics is presented to estimate road traffic states. Firstly, the representative road traffic state data were extracted to establish the reference sequences of road traffic running characteristics(RSRTRC). Secondly, the spatial road traffic state data sequence was selected and the kernel function was constructed, with which the spatial road traffic data sequence could be mapped into a high dimensional feature space. Thirdly, the referenced and current spatial road traffic data sequences were extracted and the Euclidean distances in the feature space between them were obtained. Finally, the road traffic states were estimated from weighted averages of the selected k road traffic states, which corresponded to the nearest Euclidean distances. Several typical links in Beijing were adopted for case studies. The final results of the experiments show that the accuracy of this algorithm for estimating speed and volume is 95.27% and 91.32% respectively, which prove that this road traffic states estimation approach based on kernel-KNN matching of road traffic spatial characteristics is feasible and can achieve a high accuracy.展开更多
Five trace elements including Zn, Cu, Cd, Cr and As were investigated in surface water from ten typical sampling sites in Honghu Lake. The consequence indicated that all of the detected trace element levels were withi...Five trace elements including Zn, Cu, Cd, Cr and As were investigated in surface water from ten typical sampling sites in Honghu Lake. The consequence indicated that all of the detected trace element levels were within the allowed standard of China’s safe water guideline. The hazard quotients （HQ） and the hazard index （HI） value levels of all the five heavy metals in all sampling sites did not exceed the acceptable risk limits of non-carcinogenic value through the selected assessment method. Pearson’s correlation analysis and principal component analysis （PCA） indicated that Zn and Cu mainly originated from the natural alluviation and non-point agricultural sources, whereas Cr and As were mainly derived from industrial effluents. Moreover, Cd mainly originated from both non-point agricultural and industrial pollution sources. In addition, cluster analysis （CA） implied that cluster 1 （including S3, S5, S6 and S10） was considered the set of high pollution sites and cluster 2 （including S4 and S9） was identified as the set of moderate pollution sites.展开更多
基金Projects(LQ16E080012,LY14F030012)supported by the Zhejiang Provincial Natural Science Foundation,ChinaProject(61573317)supported by the National Natural Science Foundation of ChinaProject(2015001)supported by the Open Fund for a Key-Key Discipline of Zhejiang University of Technology,China
文摘The accurate estimation of road traffic states can provide decision making for travelers and traffic managers. In this work,an algorithm based on kernel-k nearest neighbor(KNN) matching of road traffic spatial characteristics is presented to estimate road traffic states. Firstly, the representative road traffic state data were extracted to establish the reference sequences of road traffic running characteristics(RSRTRC). Secondly, the spatial road traffic state data sequence was selected and the kernel function was constructed, with which the spatial road traffic data sequence could be mapped into a high dimensional feature space. Thirdly, the referenced and current spatial road traffic data sequences were extracted and the Euclidean distances in the feature space between them were obtained. Finally, the road traffic states were estimated from weighted averages of the selected k road traffic states, which corresponded to the nearest Euclidean distances. Several typical links in Beijing were adopted for case studies. The final results of the experiments show that the accuracy of this algorithm for estimating speed and volume is 95.27% and 91.32% respectively, which prove that this road traffic states estimation approach based on kernel-KNN matching of road traffic spatial characteristics is feasible and can achieve a high accuracy.
基金Projects(51578222,51178172) supported by the National Natural Science Foundation of ChinaProjects(17Z017,17G025) supported by the Humanities and Social Science Project of Hubei Provincial Education Department,China+1 种基金Project(1718WT15) supported by the Hubei College Student Affairs Research Institute,ChinaProjects(2016J1410,2016J1411) supported by the Graduate Innovative Education Program of Zhongnan University of Economics and Law,China
文摘Five trace elements including Zn, Cu, Cd, Cr and As were investigated in surface water from ten typical sampling sites in Honghu Lake. The consequence indicated that all of the detected trace element levels were within the allowed standard of China’s safe water guideline. The hazard quotients （HQ） and the hazard index （HI） value levels of all the five heavy metals in all sampling sites did not exceed the acceptable risk limits of non-carcinogenic value through the selected assessment method. Pearson’s correlation analysis and principal component analysis （PCA） indicated that Zn and Cu mainly originated from the natural alluviation and non-point agricultural sources, whereas Cr and As were mainly derived from industrial effluents. Moreover, Cd mainly originated from both non-point agricultural and industrial pollution sources. In addition, cluster analysis （CA） implied that cluster 1 （including S3, S5, S6 and S10） was considered the set of high pollution sites and cluster 2 （including S4 and S9） was identified as the set of moderate pollution sites.
