Determination of the Gas Density in Binary Gas Mixtures Using Multivariate Data Analysis
作者： Muhammed Fatih Adak , Mustafa Akpinar , Nejat Yumusak
DOI: 10.1109/JSEN.2017.2694464
关键词: Human health 、 Bayesian multivariate linear regression 、 Solvent 、 Data set 、 Sensitivity (control systems) 、 Binary number 、 Multivariate analysis 、 Chemistry 、 Analytical chemistry 、 Multivariate analysis of variance
摘要: Some solvents in commercial products may have harmful effects on human health. It is important to determine the percentage of this certain solvent a product detect any possible health hazards. In paper, three different solvents, acetone, methanol, and chloroform, are used form binary gas mixtures laboratory environment. Nine quartz-crystal microbalance sensors used, data obtained through responses these sensors. First, set divided 11 times randomly for validation sensitivity results. For each mixtures, insignificant removed, considering multivariate analysis variance analysis, sensor sets obtained. The statistical linear regression (MvLR) method ratio individual gasses mixture. Flexible models created by removing from equations MvLR. Prediction performances reveal validate that methods can be within mixture, reliable results achieved.
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