Chemistry Department, Faculty of Science, IKIU, Qazvin, Iran.
Talanta. 2013 Jan 30;104:128-34. doi: 10.1016/j.talanta.2012.11.032. Epub 2012 Nov 20.
A rapid approach has been developed for the characterization of diesel quality, based on attenuated total reflectance - Fourier transform infrared (ATR-FTIR) spectrometry, which could be useful for diagnosing the sample quality condition. As a supervised technique, linear discriminant analysis (LDA) was employed to process the spectrometric data. The role of variable selection methods was also evaluated. Successive projection algorithm (SPA) and genetic algorithm (GA) feature selection techniques were applied prior to the discriminative procedure. It was aimed to compare the effect of feature selection procedures on classification capability of IR spectrometry for the diesel samples according to their quality passed or quality failed situation. Predictive capability of LDA was compared with that obtained by GA-LDA and SPA-LDA. Results showed 91.1%, 93.3% and 95.6% of accuracy for LDA, GA-LDA and SPA-LDA respectively. Thus SPA-LDA together with ATR-FTIR spectrometry was proposed as a fast screening analytical test for the evaluation of quality passed/failed situation in diesel samples.
已经开发出一种基于衰减全反射-傅里叶变换红外（ATR-FTIR）光谱法的柴油质量快速分析方法，该方法可用于诊断样品的质量状况。作为一种有监督的技术，线性判别分析（LDA）被用于处理光谱数据。还评估了变量选择方法的作用。在判别过程之前，应用了连续投影算法（SPA）和遗传算法（GA）特征选择技术。其目的是比较特征选择程序对根据其质量合格或不合格情况的柴油样品的红外光谱分类能力的影响。将 LDA 的预测能力与 GA-LDA 和 SPA-LDA 获得的预测能力进行了比较。结果表明，LDA、GA-LDA 和 SPA-LDA 的准确率分别为 91.1%、93.3%和 95.6%。因此，建议将 SPA-LDA 与 ATR-FTIR 光谱法结合，作为一种快速筛选分析测试方法，用于评估柴油样品的质量合格/不合格情况。
