燕山大学学报2016，Vol.40Issue(4)：360-365,6.DOI:10.3969/j.issn.1007-791X.2016.04.011
基于PSO-SVR算法的牛乳电导率近红外回归模型研究
Research on milk electrical conductivity NlR regression model based on PSO-SVR algorithm
摘要
Abstract
The rapid and accurate detection of milk electrical conductivity is of great significance to the healthy development of the dairy farm.A novel rapid detection method using near infrared spectroscopy combined with chemometrics was proposed in this paper. For the NIR spectral data of 90 farm milk samples, the support vector regression models were built by using genetic algorithm and particle swarm algorithm respectively, the results show that the PSO-SVR model has better performance and higher prediction preci-sion compared with the GA-SVR model and the traditional PLS model.The near infrared model based on PSO-SVR algorithm can be applied to the rapid and accurate measurement of the milk electrical conductivity.关键词
牛乳电导率/近红外光谱/支持向量机/粒子群算法Key words
milk electrical conductivity/NIR spectroscopy/particle swarm algorithm/support vector machine分类
化学化工引用本文复制引用
谈爱玲,赵勇,王思远,陈静雯..基于PSO-SVR算法的牛乳电导率近红外回归模型研究[J].燕山大学学报,2016,40(4):360-365,6.基金项目
河北省高等学校自然科学研究青年基金资助项目（QN2014034，Q2012129）；河北省自然科学基金资助项目（ F2014203245， F2015203270， F2014203220）；燕山大学博士基金项目 （）
