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The application of support vectors m...

Wang, Qixing.

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The application of support vectors machine (SVM) for traffic condition assessment using intelligent transportation system data.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	The application of support vectors machine (SVM) for traffic condition assessment using intelligent transportation system data./
Author:	Wang, Qixing.
Description:	55 p.
Notes:	Source: Masters Abstracts International, Volume: 49-02, page: .
Contained By:	Masters Abstracts International49-02.
Subject:	Engineering, Automotive. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1487057
ISBN:	9781124312699

The application of support vectors machine (SVM) for traffic condition assessment using intelligent transportation system data.
Wang, Qixing.

The application of support vectors machine (SVM) for traffic condition assessment using intelligent transportation system data. - 55 p.

Source: Masters Abstracts International, Volume: 49-02, page: .

Thesis (M.S.)--Texas A&M University - Kingsville, 2010.

The objective of this study is to apply data mining technology for the traffic condition prediction using the ITS data. The collected by inductive loop detectors on I-37, I-10 and I-410 in San Antonio was implemented as case study. Support Vectors Machine, a new data mining technology, is applied as the process of extracting 'Knowledge' including hidden patterns, relationship and trends between variables. The prediction results were analyzed and compared with BP neural network and traditional statistician method (Response Surface Methodology-RSM). The result showed the SVM model outperforms the best BP neural network and RSM model in terms of MAPE and the RMSE, respectively.

ISBN: 9781124312699Subjects--Topical Terms:

1018477
Engineering, Automotive.

The application of support vectors machine (SVM) for traffic condition assessment using intelligent transportation system data.
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035 $a (UMI)AAI1487057
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040 $a UMI $c UMI
100 1 $a Wang, Qixing. $3 1672576
245 1 4 $a The application of support vectors machine (SVM) for traffic condition assessment using intelligent transportation system data.
300 $a 55 p.
500 $a Source: Masters Abstracts International, Volume: 49-02, page: .
500 $a Adviser: Dazhi Sun.
502 $a Thesis (M.S.)--Texas A&M University - Kingsville, 2010.
520 $a The objective of this study is to apply data mining technology for the traffic condition prediction using the ITS data. The collected by inductive loop detectors on I-37, I-10 and I-410 in San Antonio was implemented as case study. Support Vectors Machine, a new data mining technology, is applied as the process of extracting 'Knowledge' including hidden patterns, relationship and trends between variables. The prediction results were analyzed and compared with BP neural network and traditional statistician method (Response Surface Methodology-RSM). The result showed the SVM model outperforms the best BP neural network and RSM model in terms of MAPE and the RMSE, respectively.
590 $a School code: 1187.
650 4 $a Engineering, Automotive. $3 1018477
650 4 $a Engineering, Civil. $3 783781
650 4 $a Computer Science. $3 626642
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690 $a 0543
690 $a 0984
710 2 $a Texas A&M University - Kingsville. $3 1022707
773 0 $t Masters Abstracts International $g 49-02.
790 1 0 $a Sun, Dazhi, $e advisor
790 $a 1187
791 $a M.S.
792 $a 2010
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1487057