支持向量回归在光谱分析领域的应用与研究进展

Application Research and Development of SVR in Spectral Analysis

光谱分析是化学检测领域比较成熟的分支,其应用领域多为固定少数几个工作波长进行单一成分检测。支持向量回归算法是基于机器学习的回归分析方法,结合该算法能扩大光谱分析的应用范围,能利用样品的全谱信息进行多种成分的同时检测。文章回顾了近几年来支持向量回归在化学检测领域的应用情况,并提出了今后在化学检测领域的研究方向。

Spectral analysis is an important branch of chemical analysis, the common application of spectral analysis focus on single detection wavelength, and detect single component. Support vector regression（SVR） is a regression analysis method which base on machine learning. SVR extend the application of spectral analysis in multiple components detection. We reviewed the application of SVR in spectral analysis these years, and suggest the further research direction.