A Terahertz Spectroscopy Nondestructive Identification Method for Rubber Based on CS-SVM
A method is proposed for rubber identification based on terahertz time-domain spectroscopy (THz-TDS) and support vector machine (SVM). In order to improve the accuracy, the cuckoo search algorithm (CS) is used to optimize the penalty factor C and kernel function parameter g of SVM. The SVM model opt...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi Limited
2018-01-01
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| Series: | Advances in Condensed Matter Physics |
| Online Access: | http://dx.doi.org/10.1155/2018/1618750 |
| Summary: | A method is proposed for rubber identification based on terahertz time-domain spectroscopy (THz-TDS) and support vector machine (SVM). In order to improve the accuracy, the cuckoo search algorithm (CS) is used to optimize the penalty factor C and kernel function parameter g of SVM. The SVM model optimized by the cuckoo search algorithm is abbreviated as CS-SVM. Principal component analysis (PCA) is applied to decrease the dimension of the spectral data. The top ten principal component factors, whose accumulated variance contribution rate reaches 93.93%, are extracted from the original spectra data and then are applied to CS-SVM. The identification rate of testing sets for CS-SVM is 100%, which is significantly higher than 96.67% identification rate of testing sets for PSO-SVM and Grid search. Experimental results show that CS-SVM can accomplish nondestructive identification for different rubber. This method lays a theoretical foundation for the application of terahertz spectroscopy in rubber classification and identification. |
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| ISSN: | 1687-8108 1687-8124 |