This article reports on a project in which 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 percent for discriminating between samples. PDR mapping, a new method for characterizing complex data sets, was consistent with the FuRES classification result. (publisher abstract modified)
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