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.
-
Supplemental Notes:
- Publication Date: 1999 IEEE Service Center, Piscataway NJ
-
Corporate Authors:
Texas Transportation Institute
Texas A&M University System, 3135 TAMU
College Station, TX United States 77843-3135 -
Authors:
- Chang, Edmond Chin-Ping
- Conference:
- Publication Date: 1999
Language
- English
Media Info
- Pagination: p. 2763-2767
Subject/Index Terms
- TRT Terms: Freeway management systems; Neural networks; Traffic estimation
- Subject Areas: Operations and Traffic Management;
Filing Info
- Accession Number: 00799962
- Record Type: Publication
- Source Agency: UC Berkeley Transportation Library
- Files: PATH
- Created Date: Oct 12 2000 12:00AM