ESTIMATE TRAFFIC CONTROL PATTERNS USING A HYBRID NEURAL NETWORK

In this paper, the authors focus on traffic demand prediction and traffic data modeling. They propose an approach of combining advanced neural networks and conventional error correction for improved intelligent transportation systems (ITS) applications.

Language

  • English

Media Info

  • Pagination: p. 2763-2767

Subject/Index Terms

Filing Info

  • Accession Number: 00799962
  • Record Type: Publication
  • Source Agency: UC Berkeley Transportation Library
  • Files: PATH
  • Created Date: Oct 12 2000 12:00AM