Chapter
Apr 26, 2012
Model of Highway Freight Volume Time Serial Forecast Based on Support Vector Regression
Authors: Hu Huang [email protected], Ge-fu Jiang, Yu-song Yan, and Bai-sheng LiaoAuthor Affiliations
Publication: International Conference on Transportation Engineering 2007
Abstract
To improve the forecast ability of highway freight volume, standard support vector regression (SVR) based on structural risk minimization is applied to forecasting highway freight volume. By selecting polynomial kernel function and appropriate parameters, the proposed method is used for forecasting highway freight volume of Zhengzhou city. Compared with artificial neural network (ANN) and linear regression, experimental results show that the training relative error and testing relative error obtained by SVR are lower than those by ANN and linear regression.
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Information
Published In
International Conference on Transportation Engineering 2007
Pages: 717 - 722
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
- Engineering fundamentals
- Forecasting
- Freight transportation
- Highway and road management
- Highway transportation
- Highways and roads
- Infrastructure
- Linear functions
- Mathematical functions
- Mathematics
- Models (by type)
- Neural networks
- Regression analysis
- Statistical analysis (by type)
- Statistics
- Structural models
- Transportation engineering
- Vector analysis
Authors
Affiliations
College of Logistics, Southwest Jiaotong University, Chengdu Sichuan 610031, China,. E-mail: [email protected]
Ge-fu Jiang
College of Logistics, Southwest Jiaotong University, Chengdu Sichuan 610031, China
Yu-song Yan
Sichuan Normal University, Chengdu Sichuan 610068, China
Bai-sheng Liao
College of Civil Engineering and Construction, Southwest Science and Technology University, Mianyang Sichuan 610031, China
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ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.
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Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.