Hourly road pavement surface temperature forecasting using deep learning models

Author:

Tabrizi Sepideh Emami,Xiao Kai,Van Griensven Thé Jesse,Saad Muhammad,Farghaly Hani,Yang Simon X.,Gharabaghi Bahram

Funder

Environment and Climate Change Canada

Ministère des Transports

Natural Sciences and Engineering Research Council of Canada

Publisher

Elsevier BV

Subject

Water Science and Technology

Reference43 articles.

1. Relationship between pavement temperature and weather data: Wisconsin field study to verify superpave algorithm;Bosscher;Transp. Res. Rec.,1998

2. Salt vulnerability assessment methodology for municipal supply wells;Betts;J. Hydrol.,2015

3. Salt vulnerability assessment methodology for urban streams;Betts;J. Hydrol.,2014

4. Blackburn, R.R., Bauer, K.M., Amsler, D.E., Boselly, S.E., McElory, A.D., 2004. Snow and Ice Control: Guidelines for Materials and Methods. National Cooperative Highway Research Program Report (NCHRP) 526, Transportation Research Board, Washington, D.C., 2004.

5. Buchanan, F., Gwartz, S.E. (2005). Road weather information systems at the Ministry of Transportation, Ontario. In 2005 Annual Conference of the Transportation Association of Canada, Transportation Association of Canada (TAC). Accessed on August 27, 2021 at: https://trid.trb.org/view/798228.

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