Real Time Traffic Flow Prediction and Intelligent Traffic Control from Remote Location for Large-Scale Heterogeneous NETWORKING USING TensorFlow

Abstract

Deep learning is an emerged technique to predict future and intelligent mechanism to monitor the process. Traffic Flow prediction is important function of collection traffic information and dissemination. Conventional intelligent approaches are used in large and small scalenetworks using supervised and unsupervised learning techniques.Traffic flow prediction and mitigating traffic control in remote location is an important factor in large scale networks. In this paper, we used Deep convolution neural network and Tensorflow is used to prediction of traffic flow using real time traffic data from various locations. Deep belief network is an intelligent traffic control mechanism for predicting traffic load, deep neural network and analyzing decision networks. The computer based Tensorflow is applied in deep neural networks demonstrates that our proposed supervised model is trained by deep learning approach. Our proposed model is able to achieve an improved performance in traffic flow, demonstrate large scale network traffic control using conventional l routing approach and the accuracy rate is 95% tested by Tensorflow.