光谱学与光谱分析
光譜學與光譜分析
광보학여광보분석
SPECTROSCOPY AND SPECTRAL ANALYSIS
2014年
10期
2804-2807
,共4页
紫外可见光谱%化学需氧量%潜在变量%偏最小二乘支持向量机
紫外可見光譜%化學需氧量%潛在變量%偏最小二乘支持嚮量機
자외가견광보%화학수양량%잠재변량%편최소이승지지향량궤
Ultraviolet/visible spectroscopy%Chemical oxygen demand (COD)%Latent variables (LVs)%Least square support vector machine (LS-SVM )
采用紫外可见（ultraviolet/visible ，UV/Vis）光谱技术对水体中有机物浓度的指标化学需氧量（chemical oxygen demand ，COD）进行快速检测，将收集到的135份水样进行 UV/VIS波段全光谱扫描，应用Savitzky-Golay （SG）平滑算法，经验模态分解算法（empirical modedecomposition ，EMD）和小波分析（wavelet transform ，WT ）对提取出的光谱数据进行去除噪声处理，为了简化模型，PLSR建模得到的6个潜在变量（LVs）作为偏最小二乘支持向量机（LS-SVM ）的输入建立COD预测模型，LS-SVM 模型的预测集决定系数 r2为0.82，预测均方根误差RMSEP为14.82 mg · L -1。说明使用LVs作为LS-SVM建模输入，可以准确快速检测水产养殖水体中的COD含量，为将来实现水产养殖水质COD含量的在线检测以及其他水质参数的快速测定奠定了基础。
採用紫外可見（ultraviolet/visible ，UV/Vis）光譜技術對水體中有機物濃度的指標化學需氧量（chemical oxygen demand ，COD）進行快速檢測，將收集到的135份水樣進行 UV/VIS波段全光譜掃描，應用Savitzky-Golay （SG）平滑算法，經驗模態分解算法（empirical modedecomposition ，EMD）和小波分析（wavelet transform ，WT ）對提取齣的光譜數據進行去除譟聲處理，為瞭簡化模型，PLSR建模得到的6箇潛在變量（LVs）作為偏最小二乘支持嚮量機（LS-SVM ）的輸入建立COD預測模型，LS-SVM 模型的預測集決定繫數 r2為0.82，預測均方根誤差RMSEP為14.82 mg · L -1。說明使用LVs作為LS-SVM建模輸入，可以準確快速檢測水產養殖水體中的COD含量，為將來實現水產養殖水質COD含量的在線檢測以及其他水質參數的快速測定奠定瞭基礎。
채용자외가견（ultraviolet/visible ，UV/Vis）광보기술대수체중유궤물농도적지표화학수양량（chemical oxygen demand ，COD）진행쾌속검측，장수집도적135빈수양진행 UV/VIS파단전광보소묘，응용Savitzky-Golay （SG）평활산법，경험모태분해산법（empirical modedecomposition ，EMD）화소파분석（wavelet transform ，WT ）대제취출적광보수거진행거제조성처리，위료간화모형，PLSR건모득도적6개잠재변량（LVs）작위편최소이승지지향량궤（LS-SVM ）적수입건립COD예측모형，LS-SVM 모형적예측집결정계수 r2위0.82，예측균방근오차RMSEP위14.82 mg · L -1。설명사용LVs작위LS-SVM건모수입，가이준학쾌속검측수산양식수체중적COD함량，위장래실현수산양식수질COD함량적재선검측이급기타수질삼수적쾌속측정전정료기출。
Ultraviolet/visible (UV/Vis ) spectroscopy was studied for the rapid determination of chemical oxygen demand (COD) ,which was an indicator to measure the concentration of organic matter in aquaculture water .In order to reduce the influ-ence of the absolute noises of the spectra ,the extracted 135 absorbance spectra were preprocessed by Savitzky-Golay smoothing (SG) ,EMD ,and wavelet transform (WT ) methods .The preprocessed spectra were then used to select latent variables (LVs) by partial least squares (PLS) methods .Partial least squares (PLS) was used to build models with the full spectra ,and back-propagation neural network (BPNN) and least square support vector machine (LS-SVM) were applied to build models with the selected LVs .The overall results showed that BPNN and LS-SVM models performed better than PLS models ,and the LS-SVM models with LVs based on WT preprocessed spectra obtained the best results with the determination coefficient (r2 ) and RMSE being 0.83 and 14.78 mg · L -1 for calibration set ,and 0.82 and 14.82 mg · L -1 for the prediction set respectively .The method showed the best performance in LS-SVM model .The results indicated that it was feasible to use UV/Vis with LVs which were obtained by PLS method ,combined with LS-SVM calibration could be applied to the rapid and accurate determination of COD in aquaculture water .Moreover ,this study laid the foundation for further implementation of online analysis of aquaculture water and rapid determination of other water quality parameters .
