Near Infrared Spectroscopy Analysis Based on Support Vector Machine
Min Li, Linju Lu, Jin Cao
Available Online July 2015.
- https://doi.org/10.2991/icismme-15.2015.68How to use a DOI?
- Near Infrared Spectroscopy; Multiplicative Scatter Correction; Linear Discriminant Analysis; Support Vector Machine.
- This paper put forward a kind of qualitative identification method of tea authenticity based on near infrared spectroscopy(NIR). Authentic Zhuyeqing tea and fake Zhuyeqing tea were the research objects. Multiplicative Scatter Correction (MSC) was used to NIR data of 2 kinds of Zhuyeqing tea as a pre-processing. Principal Component Analysis (PCA) was then used to spectral data for dimensionality reduction and redundant removal. Next Linear Discriminant Analysis (LDA) was used for further feature extraction. Finally Support Vector Machine (SVM) was run for identification. Rradial basis was chosen as the support vector kernel function. On the condition of , modeling recognition effect is the best of 97%. Experiments show that the algorithm can effectively identify 2 kinds of Zhuyeqing tea.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Min Li AU - Linju Lu AU - Jin Cao PY - 2015/07 DA - 2015/07 TI - Near Infrared Spectroscopy Analysis Based on Support Vector Machine BT - First International Conference on Information Sciences, Machinery, Materials and Energy PB - Atlantis Press SP - 345 EP - 348 SN - 1951-6851 UR - https://doi.org/10.2991/icismme-15.2015.68 DO - https://doi.org/10.2991/icismme-15.2015.68 ID - Li2015/07 ER -