Real time traffic flow is often difficult to predict precisely because of the complexity, nonlinearity and uncertainty characteristics of the traffic flow data. Intelligent prediction methods such as artificial neural network (ANN), support vector machine (SVM), etc. have been proven effective to discover the nonlinear information hidden in the traffic flow data. Nevertheless, a single predicti...

Multi-user traffic prediction is an important issue in broadband satellite communications system. In view of multiple UTs (User Terminal) which are treated by a single ST (Satellite Terminal), a novel NMF-based (Nonnegative Matrix Factorization-based) multi-user traffic prediction method is proposed. Compared with previous prediction schemes, the new method can reduce computational complexity a...

this paper presents the prediction of vehicle's velocity time series using neural networks. for this purpose, driving data is firstly collected in real world traffic conditions in the city of tehran using advance vehicle location devices installed on private cars. a multi-layer perceptron network is then designed for driving time series forecasting. in addition, the results of this study a...

With the rapid development of urbanization, the boom of vehicle numbers has resulted in serious traffic accidents, which led to casualties and huge economic losses. The ability to predict the risk of traffic accident is important in the prevention of the occurrence of accidents and to reduce the damages caused by accidents in a proactive way. However, traffic accident risk prediction with high ...

21 Travel-time information is an essential part of Advanced Traveler Information Systems (ATISs) 22 and Advanced Traffic Management Systems (ATMSs). A key component of these systems is the 23 prediction of travel times. From the perspective of travelers such information may assist in 24 making better route choice and departure time decisions. For transportation agencies these data 25 provide cr...

Short term traffic flow prediction has become one of the important research fields in intelligent transportation system. The prediction of this traffic flow information quickly and accurately is important for traffic control and guidance to initiate the measuring steps well in advance. It makes the transport users better informed and makes the transport network smarter, safer and more coordinat...

Traffic flow forecasting, the core element of intelligent transportation system, plays an important role in traffic information services and traffic guidance. Since neural network prediction needs plenty of training samples, it cannot guarantee the real-timeness of traffic flow forecasting. In this paper, a GMDH network was constructed by self-organization, and the network was applied to traffi...

Internet traffic prediction plays a fundamental role in network design, management, control, and optimization. The self-similar and non-linear nature of network traffic makes highly accurate prediction difficult. In this paper, a boosting-based framework is proposed for self-similar and non-linear traffic prediction by considering it as a classical regression problem. The framework is based on ...

To enhance the performance of broadband satellite networks, the application characteristics should be considered in the design of the medium access control (MAC) protocol. With the rapid expansion of Internet applications and the attractiveness of high speed Internet access via broadband satellite networks, it is important to take into account the selfsimilar nature of Internet traffic in MAC p...

Traffic Management Centers (TMC) want to improve the performance of road networks and reduce congestion by actively managing the infrastructure of a freeway corridor. A promising avenue for proactive traffic management is the prediction of the near-future traffic conditions in real-time by employing a traffic flow model. An important set of calibration parameters of such a model are the boundar...