Skip to Main content Skip to Navigation
Reports

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.
Document type :
Reports
Complete list of metadata

https://hal.inria.fr/hal-03370282
Contributor : Paola Goatin Connect in order to contact the contributor
Submitted on : Thursday, October 7, 2021 - 9:44:05 PM
Last modification on : Thursday, October 28, 2021 - 4:47:34 PM

File

RR-9426.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-03370282, version 1

Citation

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⟩

Share

Metrics

Record views

44

Files downloads

50