Application of Artificial Neural Networks for Hydrocarbon Gas Mixture Analysis

Abstract

Abstract: 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 ANNis better than that with PLS. The average prediction errors for ethane, propane and propylene were 5. 11%, 8.28%, 2. 64%, respectively, in the ANNprediction.

Key words: Artificial neural networks, PLS, Sensor array, Modeling

TrendMD:

LIN Yong-Jing, ZHU Er-Yi, LI Quan-Long, YANG Peng-Yuan. Application of Artificial Neural Networks for Hydrocarbon Gas Mixture Analysis[J]. Chem. J. Chinese Universities, 1997, 18(6): 886.

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Application of Artificial Neural Networks for Hydrocarbon Gas Mixture Analysis

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