A PERFORMANCE EVALUATION OF NEURAL NETWORK MODELS IN TRAFFIC VOLUME FORECASTING

In this paper, the authors report on studying the relationship in forecasting traffic volume between data characteristics and the forecasting accuracy of different models, with focus on neural network models. Three different data sets of traffic volume were collected in order to compare and test the forecasting accuracy of the models.

• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/08957177
• Supplemental Notes:
  • Publication Date: May-June 1998
• Corporate Authors:

  University of Maryland, College Park

  Department of Civil and Environmental Engineering
  College Park, MD  United States  20742
• Authors:
  • Yun, S Y
• Publication Date: 1998

Language

• English

Media Info

• Pagination: p. 293-310
• Serial:
  • Mathematical and computer modelling. Vol. 27, no. 9-11
  • Publisher: University of Maryland, College Park
  • ISSN: 0895-7177

Subject/Index Terms

• TRT Terms: Neural networks; Traffic estimation
• Subject Areas: Data and Information Technology;

Filing Info

• Accession Number: 00776533
• Record Type: Publication
• Source Agency: UC Berkeley Transportation Library
• Files: PATH
• Created Date: Nov 17 1999 12:00AM