期刊名称：International Journal of Advances in Engineering and Management
电子版ISSN：2395-5252
出版年度：2022
卷号：4
期号：5
页码：676-681
DOI：10.35629/5252-0405392397
语种：English
出版社：IJAEM JOURNAL
摘要：Traffic flow prediction has gained more and more attention with the rapid deployment of intelligent transportation systems (ITSs). The aim of traffic flow prediction is to provide such traffic flow information in data as well as in graphical form more meticulously. Moreover, this experiment demonstrate that the proposed method for traffic flow prediction has superior performance. In the existing systems the data are not expressed accurately. The main objective is to find a line that minimizes the prediction errors with all the data sets. Therefore, using three Machine Learning models such as LSTM, GRU and SAEs which provides the traffic flow prediction data. These data set when compared, the model SAEs shows the predicted result more meticulously.
