摘要
为快速鉴别潲水油,采用三维同步荧光光谱结合平行因子法解析潲水油的特征波长差(Δλ),并利用支持向量机建立潲水油鉴别模型。结果表明,潲水油的特征Δλ为60nm;特征Δλ下的样品原始同步荧光光谱经过主成分分析提取5个主成分,以径向基函数(RBF)为核函数,利用网格搜索和6-fold交叉验证优化建模参数,得到惩罚因子C=512、核参数g=0.5,该条件下建立的模型对训练集和预测集的判别率均达到100%。采用同步荧光光谱可以快速、准确地鉴别潲水油。
To identify hogwash oil quickly, the characteristic delta lambda of hogwash oil was analyzed by three dimensional fluorescence spectroscopy with parallel factor analysis, and the model was built up by using synchronous fluorescence spectroscopy with support vector machines (SVM). The results showed that the characteristic delta lambda of hogwash oil was 60 nm. Collecting original spectrum of different samples under the condition of characteristic delta lambda 60 nm, the best model was established while 5 principal components were selected from original spectrum and the radial basis function (RBF) was used as the kernel function, and the optimal penalty factor C and kernel function g were 512 and 0. 5 respectively obtained by the grid searching and 6-fold cross validation. The discrimination rate of the model was 100 % for both training sets and prediction sets. Thus, it is quick and accurate to apply synchronous fluorescence spectroscopy to identification of hogwash oil.
出处
《光谱学与光谱分析》
SCIE
EI
CAS
CSCD
北大核心
2012年第10期2726-2729,共4页
Spectroscopy and Spectral Analysis
基金
国家自然科学基金项目(30901129)
安徽省自然科学基金项目(1208085QC69)
安徽省农产品质量与安全特色专业基金项目(20101032)资助
关键词
潲水油
同步荧光光谱
平行因子法
支持向量机
鉴别
Hogwash oil
Synchronous fluorescence spectroscopy
Parallel factor analysis
Support vector machines
Identification