A Terahertz Spectroscopy Nondestructive Identification Method for Rubber Based on CS-SVM

作者：Yin, Xianhua; Mo, Wei; Wang, Qiang; Qin, Binyi^*

来源：Advances in Condensed Matter Physics, 2018, 2018: 1618750.

DOI：10.1155/2018/1618750

• SUPPORT VECTOR MACHINE

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.

• 出版日期2018
• 单位玉林师范学院; 桂林电子科技大学