CAJ | 학술논문

在利用红外光谱进行多组分混合气体定量分析建模中，须根据各目标气体成分的光谱特点进行光谱维数降维和特征变量选择。以甲烷、乙烷、丙烷、异丁烷、正丁烷、异戊烷和正戊烷等7种气体为分析目标，采用最小绝对收缩和选择算子(LASSO)与弹性网络(Elastic Net)方法进行目标气体数据预处理。针对LASSO和Elastic Net方法参数优化选择的问题，采用均方误差和预测偏差最小两个准则进行参数的优化选取。对4 cm-1的实测光谱数据，采用LASSO和Elastic Net方法分别在0.0019和0.0021均方误差条件下使得维度从2542维分别降为2维和3维，LASSO的交叉灵敏度最大和最小为10.2718%和1.4205%， Elastic Net分别为5.4945%和0.7493%。结果表明：Elastic Net在用于光谱定量分析的数据预处理中具有一定的优势，为准确建立定量分析模型奠定了基础。
재이용홍외광보진행다조분혼합기체정량분석건모중，수근거각목표기체성분적광보특점진행광보유수강유화특정변량선택。이갑완、을완、병완、이정완、정정완、이무완화정무완등7충기체위분석목표，채용최소절대수축화선택산자(LASSO)여탄성망락(Elastic Net)방법진행목표기체수거예처리。침대LASSO화Elastic Net방법삼수우화선택적문제，채용균방오차화예측편차최소량개준칙진행삼수적우화선취。대4 cm-1적실측광보수거，채용LASSO화Elastic Net방법분별재0.0019화0.0021균방오차조건하사득유도종2542유분별강위2유화3유，LASSO적교차령민도최대화최소위10.2718%화1.4205%， Elastic Net분별위5.4945%화0.7493%。결과표명：Elastic Net재용우광보정량분석적수거예처리중구유일정적우세，위준학건립정량분석모형전정료기출。
In the use of Fourier transform infrared spectroscopy to build the multi- component gases quantitative analysis model, it is necessary to reduce the dimensions and select characteristics wavelength according to the target gas spectral. Through the regularization algorithm analysis, least absolute shrinkage and selection operator (LASSO) and Elastic Net method were used to do these for seven kinds of mixed gases of methane, ethane, propane, iso- butane, n- butane, iso- pentane and n- pentane. The minimum mean square error (MSE) and prediction deviation were used as the criteria to select LASSO and Elastic Net parameters. Finally, the resolution of 4cm-1 measured spectral data was analyzed. The dimension of spectra were reduced from 2 542 d to 2d and 3d respectively by using LASSO and Elastic Net method under the condition of the MSE of 0.001 9 and 0.002 1. The cross sensitivity of maximum and minimum were 10.271 8% and 1.420 5% by LASSO method. The cross sensitivity of maximum and minimum were 5.494 5% and 0.749 3% by Elastic Net. Results show that the Elastic Net method was better in the characteristic variable selection and the spectral dimension reduction for gas spectral quantitative analysis,and it was foundation to establish the accurate quantitative analysis model.