TRAFFIC PREDICTION FOR INTELIGENT TRANSPORTATION USING MACHINE LEARNING









Abstract

In trendy transportation systems, a massive quantity of traffic knowledge is generated a day. This has led to speedy progress in short traffic (prediction). In traffic networks with complicated spatiotemporal relationships, deep neural networks typically perform well as a result of they're capable of mechanically extracting the foremost vital options and patterns. during this study, we tend to survey recent studies applying deep networks from four views. Keywords: Random Forest, SVM, KNN.


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Software And Hardware