Anomaly anticipation in traffic scenarios is one of the primary challenges action recognition. It believed that greater accuracy can be obtained by use semantic details and motion information along with input frames. Most state-of-the art models extract pre-defined optical flow from RGB frames combine them using deep neural networks. Many previous failed to pre-processed flow. Our study shows p...

Abstract A prediction algorithm for traffic flow prediction of BP neural based on Differential Evolution (DE) is proposed to overcome the problems such as long computing time and easy to fall into local minimum by combing DE and neural network. In the algorithm, DE is used to optimize the thresholds and weights of BP neural network, and the BP neural network is used to search for the optimal so...

The raising grandness of multimedia diligence has led to the increase in the usage of network resources. For assuring agreed Quality of Service (QoS) and for better network management, thorough analysis of traffic characteristics, modeling and prediction are crucial. In this process, a simple and effective traffic forecasting method which is suitable for time period prediction of MPEG encoded v...

A number of air traffic management decision support tools (DST) are being developed to help air traffic managers and controllers improve capacity, efficiency, and safety in the National Airspace System. Although DST functionality may vary widely, trajectory prediction algorithms can be found at the core of most DST. A methodology is presented for the automated statistical analysis of trajectory...