Ignitable liquid identification using gas chromatography/mass spectrometry data by projected difference resolution mapping and fuzzy rule-building expert system classification

The gasoline and kerosene collected from different locations in the United States were identified by gas chromatography/mass spectrometry (GC/MS) followed by chemometric analysis. Classifications based on two-way profiles and target component ratios were compared. The projected difference resolution (PDR) mapping was applied to measure the differences among the ignitable liquid (IL) samples by their GC/MS profiles quantitatively. Fuzzy rule-building expert systems (FuRESs) were applied to classify individual ILs. The FuRES models yielded correct classification rates greater than 90% for discriminating between samples. PDR mapping, a new method for characterizing complex data sets was consistent with the FuRES classification result.