Study on Support Vector Machine-Based Fault Detection in Tennessee Eastman Process
This paper investigates the proficiency of support vector machine (SVM) using datasets generated by Tennessee Eastman process simulation for fault detection. Due to its excellent performance in generalization, the classification performance of SVM is satisfactory. SVM algorithm combined with kernel...
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| Main Authors: | Shen Yin, Xin Gao, Hamid Reza Karimi, Xiangping Zhu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-01-01
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| Series: | Abstract and Applied Analysis |
| Online Access: | http://dx.doi.org/10.1155/2014/836895 |
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