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Short-term traffic flow prediction considering spatio-temporal correlation: a hybrid model combing type-2 fuzzy c-means and artificial neural network
2019
IEEE Access
Traffic flow prediction is a key step to the efficient operation in the intelligent transportation systems. This paper proposes a hybrid method combing clustering methods and spatiotemporal correlation to predict future traffic trends based on artificial neural network. First, for the traffic flow collected from different loop detectors, a spatio-temporal correlation of data samples is evaluated by considering time correlation and spatial equivalent distance. Second, in order to improve
doi:10.1109/access.2019.2931920
fatcat:uldisdmew5gqre2vdsu5szkqg4