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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Zhili Cai Qiushi Ding Mingting Wang |
| Copyright Year | 2010 |
| Abstract | According to the freeway traffic flow characteristics under incidents situation, this paper puts forward a kind of AID algorithm based on PCA & SVM. Above all, PCA has been applied to extract principle components from preselected indexes, to realize dimension reductions, and construct the traffic eigenvectors. And then, validity of the new algorithm proposed in this paper has been tested using various SVM models, and also contrasts with the results of algorithms only based on SVM. The simulation results demonstrate that the new algorithm can detect incidents more effectively and more expeditiously, with the preferable detection performance. Especially, detection effects of the new algorithm based on linear SVMmodels are the best. |
| Starting Page | 420 |
| Ending Page | 424 |
| File Size | 300430 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424486830 |
| DOI | 10.1109/ICOIP.2010.124 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-11-11 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Support vector machines Algorithm design and analysis Automated Incident Detection (AID) Support Vector Machine (SVM) Freeway Intelligent Transportation Systems (ITS) Approximation algorithms Data models Principal Component Analysis (PCA) Indexes Kernel Principal component analysis |
| Content Type | Text |
| Resource Type | Article |
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