An array of nine piezoelectric quartz crystals, each coated with a different derivative compound of crown-ether, was constructed for mullticomponent analysis of organic vapors. The usefulness of this array was evaluated by quantitating known mixture samples in both two and three component 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.

Key words: SENSORS, LEAST SQUARE METHODS, PIEZOELECTRIC CRYSTALS, PATTERN RECOGNITION, CROWN ETHER, NEURAL NETWORK