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Corrosion Depth Prediction Based on SVM and Chaos
LIANG Ping 1,RAO Guoran 2 * #,LONG Xinfeng 2
1.School of Electricity Power，South China University of Technology
2.South China University of Technology
*Correspondence author
#Submitted by
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Funding: none
Opened online:10 February 2009
Accepted by: none
Citation: LIANG Ping,RAO Guoran,LONG Xinfeng.Corrosion Depth Prediction Based on SVM and Chaos[OL]. [10 February 2009] http://en.paper.edu.cn/en_releasepaper/content/28646
 
 
Pipeline of oil and gas have an increase risk because of pipeline punctures and rupture caused by corrosion. Therefore, it is very important to have a reliable way for pipeline corrosion prediction. The corrosion depth prediction models that based on the support vector machines and based on chaos were introduced in this paper. A real example was given in this paper, and the corrosion data were obtained by electricity probe. The predicted results shows that prediction has a more high precision. The prediction ways based the support vector machines and chaos are reasonable in the corrosion research, which can supply a scientific basis for pipeline safety management, service life prediction and repair.
Keywords:corrosion depth; SVM; chaos; forecasting
 
 
 

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