Traffic Velocity Prediction Using GPS Data: IEEE ICDM Contest Task 3 Report
This report summarizes the methodologies and techniques we developed and applied for tackling task 3 of the IEEE ICDM Contest on predicting traffic velocity based on GPS data. The major components of our solution include 1) A pre-processing procedure to map GPS data to the network, 2) A K-nearest ne...
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| creator | Wei Shen Kamarianakis, Y Wynter, L Jingrui He Qing He Lawrence, R Swirszcz, G |
| description | This report summarizes the methodologies and techniques we developed and applied for tackling task 3 of the IEEE ICDM Contest on predicting traffic velocity based on GPS data. The major components of our solution include 1) A pre-processing procedure to map GPS data to the network, 2) A K-nearest neighbor approach for identifying the most similar training hours for every test hour, and 3) A heuristic evaluation framework for optimizing parameters and avoiding over-fitting. Our solution finished Second in the final evaluation. |
| doi_str_mv | 10.1109/ICDMW.2010.52 |
| format | Conference Proceeding |
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| ispartof | 2010 IEEE International Conference on Data Mining Workshops, 2010, p.1369-1371 |
| issn | 2375-9232 2375-9259 |
| language | eng |
| recordid | cdi_ieee_primary_5693455 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | cross validation Data models Global Positioning System Harmonic analysis map-matching nearest neighbor Predictive models Roads Training Vehicles |
| title | Traffic Velocity Prediction Using GPS Data: IEEE ICDM Contest Task 3 Report |
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