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Road Traffic Data analysis: Clustering and Prediction

Abstract : This document presents a clustering and prediction analysis on daily time series of traffic data taken from loop detector measurement at different location (France and USA). It shows the effectiveness of Soft Dynamic Time Warping and K-means algorithm for clustering and Support Vector Regression for prediction on the selected data sets. Results are commented to get information on specific traffic dynamics.
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Reports (Research report)
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Contributor : Paola Goatin Connect in order to contact the contributor
Submitted on : Thursday, October 7, 2021 - 9:44:05 PM
Last modification on : Wednesday, October 26, 2022 - 8:15:35 AM
Long-term archiving on: : Saturday, January 8, 2022 - 7:47:05 PM


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  • HAL Id : hal-03370282, version 1


Nicola Ronzoni, Paola Goatin. Road Traffic Data analysis: Clustering and Prediction. [Research Report] RR-9426, Inria; Unniversité Ctote d'Azur; CNRS; I3S. 2021. ⟨hal-03370282⟩



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