Methodology to Forecast Road Surface Temperature with Principal Components Analysis and Partial Least-Square Regression: Application to an Urban Configuration
Joint Authors
Marchetti, M.
Khalifa, Abderrahmen
Buès, Michel
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-06-09
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
A forecast road surface temperature (RST) helps winter services to optimize costs and to reduce the deicers environmental impacts.
Data from road weather information systems (RWIS) and thermal mapping are considered inputs for forecasting physical numerical models.
Statistical models include many meteorological parameters along routes and provide a spatial approach.
It is based on typical combinations resulting from treatment and analysis of a database from measurements of road weather stations or thermal mapping, easy, reliable, and cost effective to monitor RST, and many meteorological parameters.
A forecast dedicated to road networks should combine both spatial and time forecasts needs.
This study contributed to building a reliable RST forecast based on principal component analysis (PCA) and partial least-square (PLS) regression.
An urban stretch with various weather conditions and seasons was monitored over several months to generate an appropriate number of samples.
The study first consisted of the identification of its optimum number to establish a reliable forecast.
A second aspect is aimed at comparing RST forecasts from PLS model to measurements.
Comparison indicated a forecast over an urban stretch with up to 94% of values within ±1°C and over 80% within ±3°C.
American Psychological Association (APA)
Marchetti, M.& Khalifa, Abderrahmen& Buès, Michel. 2015. Methodology to Forecast Road Surface Temperature with Principal Components Analysis and Partial Least-Square Regression: Application to an Urban Configuration. Advances in Meteorology،Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1052770
Modern Language Association (MLA)
Marchetti, M.…[et al.]. Methodology to Forecast Road Surface Temperature with Principal Components Analysis and Partial Least-Square Regression: Application to an Urban Configuration. Advances in Meteorology No. 2015 (2015), pp.1-10.
https://search.emarefa.net/detail/BIM-1052770
American Medical Association (AMA)
Marchetti, M.& Khalifa, Abderrahmen& Buès, Michel. Methodology to Forecast Road Surface Temperature with Principal Components Analysis and Partial Least-Square Regression: Application to an Urban Configuration. Advances in Meteorology. 2015. Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1052770
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1052770