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
In this study, two deep convective cloud cases were analyzed in detail to study their initiation and evolution. In both cases, all deep convective clouds were positioned at the rear of the cold front cloud bands and p...In this study, two deep convective cloud cases were analyzed in detail to study their initiation and evolution. In both cases, all deep convective clouds were positioned at the rear of the cold front cloud bands and propagated backward. Satellite data showed that prior to initiation of the deep convective clouds, thermodynamic and moist conditions were favorable for their formation. In the morning, a deep convective cloud at the rear of cold front cloud band propagated backward, the outflow boundary of which created favorable conditions for initiation. An additional deep convective cloud cluster moved in from the west and interacted with the outflow boundary to develop a mesoscale convective system(MCS) with large, ellipse-shaped deep convective clouds that brought strong rainfall. The initiation and evolution of these clouds are shown clearly in satellite data and provide significant information for nowcasting and short-term forecasting.展开更多
This paper.fi＇rst conducts a systematic review of domestic and foreign scholars＇ approaches to predicting short-term capital flows, then employs a combination of both direct and indirect methods to carry out its ana...This paper.fi＇rst conducts a systematic review of domestic and foreign scholars＇ approaches to predicting short-term capital flows, then employs a combination of both direct and indirect methods to carry out its analysis. Three kinds of indicators, both specific and general, are applied in both methods. Thorough consideration is given to short-term international capital inflow from trade, other current account items, capital account, and errors and omissions, as well as other channels through which short term capital might accrue to a nation＇s balance. Based on a comprehensive comparison of year-on-year data, this paper also estimates monthly data using a simplified, indirect calculation approach. Estimates show that, despite a degree of difference in results between methods, most estimates are highly consistent for a given period. Based on monthly estimates, we conclude that turbulence in international financial markets （i.e., the United States subprime mortgage crisis and the European sovereign debt crisis） has had a major impact on China ＇s short-term capital flow.展开更多
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.
基金supported by the National Natural Science Foundation of China"Study of Characteristics of the Environmental Field before the Deep Convective Cloud Initiated Using Geostational Meteorological Satellite Data"(Grant No.41005026)
文摘In this study, two deep convective cloud cases were analyzed in detail to study their initiation and evolution. In both cases, all deep convective clouds were positioned at the rear of the cold front cloud bands and propagated backward. Satellite data showed that prior to initiation of the deep convective clouds, thermodynamic and moist conditions were favorable for their formation. In the morning, a deep convective cloud at the rear of cold front cloud band propagated backward, the outflow boundary of which created favorable conditions for initiation. An additional deep convective cloud cluster moved in from the west and interacted with the outflow boundary to develop a mesoscale convective system(MCS) with large, ellipse-shaped deep convective clouds that brought strong rainfall. The initiation and evolution of these clouds are shown clearly in satellite data and provide significant information for nowcasting and short-term forecasting.
文摘This paper.fi＇rst conducts a systematic review of domestic and foreign scholars＇ approaches to predicting short-term capital flows, then employs a combination of both direct and indirect methods to carry out its analysis. Three kinds of indicators, both specific and general, are applied in both methods. Thorough consideration is given to short-term international capital inflow from trade, other current account items, capital account, and errors and omissions, as well as other channels through which short term capital might accrue to a nation＇s balance. Based on a comprehensive comparison of year-on-year data, this paper also estimates monthly data using a simplified, indirect calculation approach. Estimates show that, despite a degree of difference in results between methods, most estimates are highly consistent for a given period. Based on monthly estimates, we conclude that turbulence in international financial markets （i.e., the United States subprime mortgage crisis and the European sovereign debt crisis） has had a major impact on China ＇s short-term capital flow.
