Link Travel Time Prediction Based on the Integration of Rough Set and BP Neural Network

Link travel time prediction is a focus of intelligent transportation system (ITS) research. Through comparing the performances of the existing prediction algorithm, this article tries to integrate rough set and BP neural network to establish a new one for link travel time prediction. By comparing the predicted values of travel time to the real travel time, the predicted model is verified to be effective.

• Record URL:
  https://doi.org/10.1061/41039(345)78
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784410394
• Supplemental Notes:
  • © 2009 American Society of Civil Engineers.
• Corporate Authors:

  American Society of Civil Engineers

  1801 Alexander Bell Drive
  Reston, VA  United States  20191-4400
• Authors:
  • Chen, Yao
  • Henk, J Van Zuylen
  • Luo, Xia
  • Liu, Haixu
• Conference:
  • Second International Conference on Transportation Engineering
  • Location: Chengdu , China
  • Date: 2009-7-25 to 2009-7-27
• Publication Date: 2009-7

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 470-475
• Monograph Title: International Conference on Transportation Engineering 2009

Subject/Index Terms

• TRT Terms: Algorithms; Intelligent transportation systems; Mathematical prediction; Neural networks; Travel time
• Subject Areas: Data and Information Technology; Operations and Traffic Management; Transportation (General); I70: Traffic and Transport;

Filing Info

• Accession Number: 01535842
• Record Type: Publication
• ISBN: 9780784410394
• Files: TRIS, ASCE
• Created Date: Nov 12 2013 1:47PM