An array composed of sixtorganiceen metal oxide semiconductor gas sensors was constructed to analyze gas mixtures quantitatively.The responses of the sensor array to ethane, propane and propylene were treated by three-layer artiFicial neural networks (ANN)with the method of error back-propagation and partial least-squares (PLS)- The pattern recognition results indicated that the concentration predicted with ANN is better than that with PLS.The average prediction errors For ethane, propane and propylene were 5.11%, 8.28%, 2.64%, respectively, in the ANN prediction.国家自然科学基金;福建省自然科学资
