Short-term travel flow prediction has been the core of the intelligent transport systems(ITS). An advanced method based on fuzzy C-means(FCM) and extreme learning machine(ELM) has been discussed by analyzing predictio...Short-term travel flow prediction has been the core of the intelligent transport systems(ITS). An advanced method based on fuzzy C-means(FCM) and extreme learning machine(ELM) has been discussed by analyzing prediction model. First, this model takes advantages of ability to adapt to nonlinear systems and the fast speed of ELM algorithm. Second, with FCM-clustering function, this novel model can get the clusters and the membership in the same cluster, which means that the associated observation points have been chosen. Therefore, the spatial relations can be used by giving the weight to every observation points when the model trains and tests the ELM. Third, by analyzing the actual data in Haining City in 2016, the feasibility and advantages of FCM-ELM prediction model have been shown when compared with other prediction algorithms.展开更多
In this paper, author considers a 3 x 3 system for a reacting flow model propesed by [9]. Since this model has source term, it can be considered as a relaxation approximation to 2 x 2 systems of conservation laws, whi...In this paper, author considers a 3 x 3 system for a reacting flow model propesed by [9]. Since this model has source term, it can be considered as a relaxation approximation to 2 x 2 systems of conservation laws, which include the well-known p-system. From this viewpoint, the author establishes the global existence and the nonlinear stability of travelling wave solutions by L-2 energy method.展开更多
Metro system has experienced the global rapid rise over the past decades. However,few studies have paid attention to the evolution in system usage with the network expanding. The paper's main objectives are to ana...Metro system has experienced the global rapid rise over the past decades. However,few studies have paid attention to the evolution in system usage with the network expanding. The paper's main objectives are to analyze passenger flow characteristics and evaluate travel time reliability for the Nanjing Metro network by visualizing the smart card data of April 2014,April 2015 and April 2016. We performed visualization techniques and comparative analyses to examine the changes in system usage between before and after the system expansion. Specifically,workdays,holidays and weekends were specially segmented for analysis.Results showed that workdays had obvious morning and evening peak hours due to daily commuting,while no obvious peak hours existed in weekends and holidays and the daily traffic was evenly distributed. Besides,some metro stations had a serious directional imbalance,especially during the morning and evening peak hours of workdays. Serious unreliability occurred in morning peaks on workdays and the reliability of new lines was relatively low,meanwhile,new stations had negative effects on exiting stations in terms of reliability. Monitoring the evolution of system usage over years enables the identification of system performance and can serve as an input for improving the metro system quality.展开更多
In this paper, a coordinate transformation method (CTM) is employed to numerically solve the Poisson–Nernst–Planck (PNP) equation and Navier–Stokes (NS) equations for studying the traveling-wave electroosmotic flow...In this paper, a coordinate transformation method (CTM) is employed to numerically solve the Poisson–Nernst–Planck (PNP) equation and Navier–Stokes (NS) equations for studying the traveling-wave electroosmotic flow (TWEF) in a two-dimensional microchannel. Numerical solutions indicate that the numerical solutions of TWEF with and without the coordinate transformation are in good agreement, while CTM effectively improves stability and convergence rate of the numerical solution, and saves computational cost. It is found that the averaged flow velocity of TWEF in a micro-channel strongly depends on frequency of the electric field. Flow rate achieves a maximum around the charge frequency of the electric double layer. The approximate solutions of TWEF with slip boundary conditions are also presented for comparison. It is shown that the NS solution with slip boundary conditions agree well with those of complete PNP-NS equations in the cases of small ratios of Electric double layer(EDL) thickness to channel depth(λD/H). The NS solution with slip boundary conditions over-estimates the electroosmotic flow velocity as this ratio(λD/H) is large.展开更多
Traffic flow prediction is an important component for real-time traffic-adaptive signal control in urban arterial networks.By exploring available detector and signal controller information from neighboring intersectio...Traffic flow prediction is an important component for real-time traffic-adaptive signal control in urban arterial networks.By exploring available detector and signal controller information from neighboring intersections,a dynamic data-driven flow prediction model was developed.The model consists of two prediction components based on the signal states(red or green) for each movement at an upstream intersection.The characteristics of each signal state were carefully examined and the corresponding travel time from the upstream intersection to the approach in question at the downstream intersection was predicted.With an online turning proportion estimation method,along with the predicted travel times,the anticipated vehicle arrivals can be forecasted at the downstream intersection.The model performance was tested at a set of two signalized intersections located in the city of Gainesville,Florida,USA,using the CORSIM microscopic simulation package.Analysis results show that the model agrees well with empirical arrival data measured at 10 s intervals within an acceptable range of 10%-20%,and show a normal distribution.It is reasonably believed that the model has potential applicability for use in truly proactive real-time traffic adaptive signal control systems.展开更多
基金Project(2016YFB0100906)supported by the National Key R&D Program in ChinaProject(2014BAG03B01)supported by the National Science and Technology Support plan Project China+1 种基金Project(61673232)supported by the National Natural Science Foundation of ChinaProjects(Dl S11090028000,D171100006417003)supported by Beijing Municipal Science and Technology Program,China
文摘Short-term travel flow prediction has been the core of the intelligent transport systems(ITS). An advanced method based on fuzzy C-means(FCM) and extreme learning machine(ELM) has been discussed by analyzing prediction model. First, this model takes advantages of ability to adapt to nonlinear systems and the fast speed of ELM algorithm. Second, with FCM-clustering function, this novel model can get the clusters and the membership in the same cluster, which means that the associated observation points have been chosen. Therefore, the spatial relations can be used by giving the weight to every observation points when the model trains and tests the ELM. Third, by analyzing the actual data in Haining City in 2016, the feasibility and advantages of FCM-ELM prediction model have been shown when compared with other prediction algorithms.
文摘In this paper, author considers a 3 x 3 system for a reacting flow model propesed by [9]. Since this model has source term, it can be considered as a relaxation approximation to 2 x 2 systems of conservation laws, which include the well-known p-system. From this viewpoint, the author establishes the global existence and the nonlinear stability of travelling wave solutions by L-2 energy method.
基金Sponsored by Projects of International Cooperation and Exchange of the National Natural Science Foundation of China(Grant No.51561135003)Key Project of National Natural Science Foundation of China(Grant No.51338003)
文摘Metro system has experienced the global rapid rise over the past decades. However,few studies have paid attention to the evolution in system usage with the network expanding. The paper's main objectives are to analyze passenger flow characteristics and evaluate travel time reliability for the Nanjing Metro network by visualizing the smart card data of April 2014,April 2015 and April 2016. We performed visualization techniques and comparative analyses to examine the changes in system usage between before and after the system expansion. Specifically,workdays,holidays and weekends were specially segmented for analysis.Results showed that workdays had obvious morning and evening peak hours due to daily commuting,while no obvious peak hours existed in weekends and holidays and the daily traffic was evenly distributed. Besides,some metro stations had a serious directional imbalance,especially during the morning and evening peak hours of workdays. Serious unreliability occurred in morning peaks on workdays and the reliability of new lines was relatively low,meanwhile,new stations had negative effects on exiting stations in terms of reliability. Monitoring the evolution of system usage over years enables the identification of system performance and can serve as an input for improving the metro system quality.
文摘In this paper, a coordinate transformation method (CTM) is employed to numerically solve the Poisson–Nernst–Planck (PNP) equation and Navier–Stokes (NS) equations for studying the traveling-wave electroosmotic flow (TWEF) in a two-dimensional microchannel. Numerical solutions indicate that the numerical solutions of TWEF with and without the coordinate transformation are in good agreement, while CTM effectively improves stability and convergence rate of the numerical solution, and saves computational cost. It is found that the averaged flow velocity of TWEF in a micro-channel strongly depends on frequency of the electric field. Flow rate achieves a maximum around the charge frequency of the electric double layer. The approximate solutions of TWEF with slip boundary conditions are also presented for comparison. It is shown that the NS solution with slip boundary conditions agree well with those of complete PNP-NS equations in the cases of small ratios of Electric double layer(EDL) thickness to channel depth(λD/H). The NS solution with slip boundary conditions over-estimates the electroosmotic flow velocity as this ratio(λD/H) is large.
基金Project(71101109) supported by the National Natural Science Foundation of China
文摘Traffic flow prediction is an important component for real-time traffic-adaptive signal control in urban arterial networks.By exploring available detector and signal controller information from neighboring intersections,a dynamic data-driven flow prediction model was developed.The model consists of two prediction components based on the signal states(red or green) for each movement at an upstream intersection.The characteristics of each signal state were carefully examined and the corresponding travel time from the upstream intersection to the approach in question at the downstream intersection was predicted.With an online turning proportion estimation method,along with the predicted travel times,the anticipated vehicle arrivals can be forecasted at the downstream intersection.The model performance was tested at a set of two signalized intersections located in the city of Gainesville,Florida,USA,using the CORSIM microscopic simulation package.Analysis results show that the model agrees well with empirical arrival data measured at 10 s intervals within an acceptable range of 10%-20%,and show a normal distribution.It is reasonably believed that the model has potential applicability for use in truly proactive real-time traffic adaptive signal control systems.
