This article discusses the use of big traffic data to predict traffic states on a suburban road in Iran. The study utilizes various methods such as principal component analysis and genetic algorithms to manage the large volume and variety of data. The results show that using cyclic features can significantly increase the accuracy of traffic state prediction.
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