By Topic

Wavelet network with genetic algorithm and its applications for traffic flow forecasting

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Licai Yang ; Sch. of Control Sci. & Eng., Shandong Univ., Jinan, China ; Lei Jia ; Hong Wang

Real-time and accurate traffic flow forecasting is very important to the intelligent traffic guidance, control and management. According to the characteristics of traffic flow, this paper proposes a new model of traffic flow forecasting based on wavelet networks and the forecasting algorithm of comparable time intervals. The structures of wavelet networks are optimized with genetic algorithm. The experiment results show that this model is superior to the common BP neural networks in the aspects of flow forecasting precision and network convergence.

Published in:

Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on  (Volume:6 )

Date of Conference:

15-19 June 2004