It is an important to quickly and accurately forecasting road network traffic flow in intelligent transportation systems, Aiming at the forecasting problem of short-term traffic flow, this paper proposed a traffic flow prediction algorithm, which based on traffic flow sequence partition and neural network model. Firstly, the algorithm divided the traffic flow into different patterns and time se...

Fast and accurate network traffic identification is becoming essential for network management, high quality of service control and early detection of network traffic abnormalities. Techniques based on statistical features of packet flows have recently become popular for network classification due to the limitations of traditional port and payload based methods. In this paper, we propose a metho...

Nowadays the active traffic management is enabled for better performance due to the nature of the real-time large data in transportation system. With the advancement of large data, monitoring and improving the traffic safety transformed into necessity in the form of actively and appropriately. Per-formance efficiency and traffic safety are considered as an im-portant element in measuring the pe...

Real time internet traffic classification is imperative for service discrimination, network security and network monitoring. Classification of traffic depends on initial first few network packets of full flows of captured IP traffic. Practically, the real world framework situation expects correct conclusion of classification well before a flow has ended even if the start of the Traffic flow is ...

A novel approach to sector capacity prediction for airspace congestion management is presented, in which traffic complexity is captured with traffic flow patterns. Predictability of flow features are quantified and considered in describing the traffic flow patterns. Quantifying sector capacity as a function of traffic flow pattern provides a good approximation of the amount of traffic that can ...