… We focused on how to systematically resolve a traffic … by the traffic control problem without
human intervention in practice, we present a traffic control system based on machine learning-…

… machine learning), and we apply it as a tool to improve the traffic incident response and
optimize the traffic signal control plan during incidents. The method is applied for a case study …

… trackers, traditional traffic control lights, continuous pollution check, human tracking, etc. but
the theses classical traffic management techniques had failed to ensure operative traffic flow …

… Especially in [14], the machine learning algorithm including the aircraft … in the machine
learning for the delay prediction [15]. In this study, the airborne delay due to the air traffic control (…

… Intelligence and Machine Learning paradigms. Our focus, in this paper, … art deep learning
techniques. Second, we identify the various network traffic control themes where deep learning …

… learning) in Section III. In the third part of Section IV, we survey the machine learning based
adaptive streaming control … , the machine learning based adaptive streaming control for endto…

… be enhanced by learning from historical data. Nowadays, data from the Air Traffic Management
system may be exploited to understand to what extent Air Traffic Control actions impact …

… of research to monitor road traffic congestion and traffic control have been suggested in the
… Using a real-time dynamic traffic control scheme to route vehicles smartly will improve traffic …

… In this work, we use a scalable machine learning system for tree boosting, called XGBoost.
It has been widely used in a number of machine learning and data mining challenges with …

… We have put forth a review on machine learning-based traffic control force scheduling,
which ensures the optimal utilization of human resources (employment), money, time, and non-…