|Table of Contents|

Parameter selection of support vector machine based on stepped-up chaos optimization algorithm(PDF)

《交通运输工程学报》[ISSN:1671-1637/CN:61-1369/U]

Issue:
2010年02期
Page:
122-126
Research Field:
交通信息工程及控制
Publishing date:
2010-04-20

Info

Title:
Parameter selection of support vector machine based on stepped-up chaos optimization algorithm
Author(s):
LI Dong-qin1;  3;  WANG Li-zheng2;  GUAN Yi-feng1;  XU Hai-xiang2
1. School of Naval Architecture and Ocean Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003, Jiangsu, China; 2. School of Transportation, Wuhan University of Technology, Wuhan 430063, Hubei, China; 3. Jiangsu Modern Shipbuilding Technology Ltd., Zhenjiang 212003, Jiangsu, China
Keywords:
support vector machine;  stepped-up chaos optimization;  parameter optimization;  throughput prediction
PACS:
U652.14
DOI:
-
Abstract:
In order to analyze the parameter selection of support vector machine(SVM), penalty coefficient, insensitive coefficient and width coefficient in radial basis function(RBF)were used as optimization variables, the former searching formula was changed, and the third searching time was added. A new improved stepped-up chaos optimization algorithm(ISCOA)was proposed by adopting the Chebyshev mapping instead of Logistic mapping to form initial chaos serial. The new algorithm was used in artificial data set and real data set, and was compared with traditional cross validation method. Test result indicates that the running time is cut down at least 23.43%, and the precision improves at least 6.31% by using ISCOA in artificial data set. The predicted value is more close to real value, and the relative errors are controlled under 3.13% in real data set. So ISCOA has higher prediction precision and optimization effect. 3 tabs, 3 figs, 12 refs.

References:

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Memo:
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Last Update: 2010-04-20