USING AN ARTIFICIAL NEURAL NETWORK TO PREDICT PARAMETERS FOR FROST DEPOSITION ON IOWA BRIDGEWAYS

This paper investigates a new method for forecasting frost formation on Iowa bridgeways. A frost model developed by Knollhoff et al. (2001) predicts frost deposition based on moisture flux principles. The frost model requires 4 inputs: air temperature; dew-point temperature; wind speed; and surface temperature. An artificial neural network is used to predict these four inputs at 20-minute intervals for a 24-hour period. The output from the neural network models can then be used as input into the frost deposition model to predict frost formation on Iowa bridgeways. The proper development of an artificial neural network requires the dataset to be subdivided into at least a training set and a validation set. A test set can also be used to further test the model. Results showed that the predictions correlated well with the road weather information system observations, and generally perform better than output from nested grid model-model output statistics alone.

• Record URL:
  http://www.ctre.iastate.edu/pubs/midcon2003/TemeyerFrost.pdf
• 
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/0965231062
• Corporate Authors:

  Iowa State University, Ames

  Center for Transportation Research and Education
  2711 South Loop Drive, Suite 4700
  Ames, IA  United States  50010-8664
• Authors:
  • Temeyer, B R
  • Gallus Jr, W A
  • Jungbluth, K A
  • Burkheimer, D
  • McCauley, D
• Conference:
  • Mid-Continent Transportation Research Symposium
  • Location: Ames, Iowa
  • Date: 2003-8-21 to 2003-8-22
• Publication Date: 2003

Language

• English

Media Info

• Features: Figures; References; Tables;
• Pagination: 6p
• Monograph Title: MID-CONTINENT TRANSPORTATION RESEARCH SYMPOSIUM (AMES, IOWA, AUGUST 21-22, 2003). PROCEEDINGS

Subject/Index Terms

• TRT Terms: Atmospheric temperature; Bridges; Dew point; Frost; Mathematical prediction; Neural networks; Road weather information systems; Surface temperature; Weather conditions; Weather forecasting
• Uncontrolled Terms: Wind speed
• Geographic Terms: Iowa
• Subject Areas: Bridges and other structures; Data and Information Technology; Highways; Maintenance and Preservation; I62: Winter Maintenance;

Filing Info

• Accession Number: 00964694
• Record Type: Publication
• ISBN: 0965231062
• Files: TRIS
• Created Date: Oct 14 2003 12:00AM