ORGANIC VAPOR MIXTURE DETECTION WITH PIEZ OELECTRIC CRYSTAL SENSOR ARRAY USING PATTERN-RECOGNITION TECHNIQUES

At array of nine piezoelectric quartz crystals, each coated with a dif ferent derivative compound of crown-ether, was constructed for multico mponent analysis of organic vapors. The usefulness of this array was e valuated by quantitating known mixture samples in both two and three c omponent cases using two chemometric techniques, partial least squares (PLS) and artificial neural networks (ANN). The results show that the prediction was better for ANN in both two and three component cases. The method to avoid overfitting in ANN training was also discussed.