Chapter
Apr 26, 2012
The Combined Short-Term Forecasting Approach to Traffic Flow Based on Non-Parametric Regression
Authors: Xiao-li Zhang [email protected] and School of Management, Hebei University, Hebei province Baoding 071002, China and Guo-guang HeAuthor Affiliations
Publication: International Conference on Transportation Engineering 2007
Abstract
A combined method based on of Principal Component Analysis (PCA), Subtraction Fuzzy Clustering (SFC), and Non-Parametric Regression (NPR) is proposed in view of nonlinearity and uncertainty for short-term forecasting of real-time traffic flow. A highly efficient case database is created from the original traffic volumes after the operations of PCA and SFC. The data-driven method of K-nearest neighbours NPR is used to make the forecasting. An emulation experiment is designed to test the validity of the method. The example results show it is better than normal NPR and meets real-time requirement.
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Published In
International Conference on Transportation Engineering 2007
Pages: 130 - 135
Copyright
© 2007 American Society of Civil Engineers.
History
Published online: Apr 26, 2012
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ASCE Technical Topics:
- Analysis (by type)
- Artificial intelligence and machine learning
- Computer programming
- Computing in civil engineering
- Continuum mechanics
- Dynamics (solid mechanics)
- Engineering fundamentals
- Engineering mechanics
- Forecasting
- Fuzzy logic
- Infrastructure
- Mathematics
- Motion (dynamics)
- Nonlinear analysis
- Parameters (statistics)
- Regression analysis
- Solid mechanics
- Statistical analysis (by type)
- Statistics
- Structural analysis
- Structural engineering
- Traffic analysis
- Traffic engineering
- Traffic flow
- Traffic management
- Transportation engineering
- Uncertainty principles
Authors
Affiliations
Xiao-li Zhang [email protected] and School of Management, Hebei University, Hebei province Baoding 071002, China
Institute of Systems Engineering, Tianjin University, Tianjin 300072, China. E-mail: [email protected] and School of Management, Hebei University, Hebei province Baoding 071002, China
Guo-guang He
Institute of Systems Engineering, Tianjin University, Tianjin 300072, China
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