Abstract
The fuzzy c-means (FCM) clustering models were used for the discrimination of organic compounds using piezoelectric chemical sensor array data of 14 analytes. Appropriate clusters are found by the sum of the weighted quadratic distances between data points and cluster prototypes. A priori known information can be integrated into the clustering algorithm by using constrained prototypes. A sensor array was built using piezoelectric quartz crystal sensors. Four AT-cut quartz crystals with 9 MHz fundamental frequencies were applied. Sensing materials were OV1, OV275, ASI50, and polyphenil-ether. The appropriate coating materials were found by principal component analysis. The application of the fuzzy clustering method has been proved to be a reliable way of identifying similar, pure organic compounds.
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