| Delay characteristics and refractive index characteristics of four kinds of edible oils (black sesame oil, traditional sesame oil, sesame oil, peanut oil) in the range of 0.2-1.6 THz were investigated by terahertz time-domain spectroscopy(THz-TDS).Principal component analysis (PCA) was employed to extract feature data according to the accumulative contribution rates. The top four principal components (accumulative contribution rate above 95%) were selected, and then a support vector machine (SVM) method was applied. The results showed that by choosing the appropriate kernel function and its parameters of SVM, the samples were identified with an accuracy of 93%.Furthermore, compared with principal component regression, partial least squares regression, and back-propagation neural networks, PCA-SVM had a more prominent classification performance and also indicated that the THz-TDS technology combined with PCA-SVM was efficient and feasible for identifying different kinds of edible oils. |
