高等学校化学学报 ›› 1997, Vol. 18 ›› Issue (6): 886.

• 研究简报 • 上一篇    下一篇

烃类混合气体的神经网络模型检测

林雍静, 朱尔一, 李权龙, 杨芃原   

  1. 厦门大学化学系分析科学国家教育委员会开放实验室, 厦门, 361005
  • 收稿日期:1996-07-03 出版日期:1997-06-24 发布日期:1997-06-24
  • 通讯作者: 杨芃原.
  • 作者简介:林雍静, 女, 23岁, 硕士研究生.
  • 基金资助:

    国家自然科学基金;福建省自然科学资助

Application of Artificial Neural Networks for Hydrocarbon Gas Mixture Analysis

LIN Yong-Jing, ZHU Er-Yi, LI Quan-Long, YANG Peng-Yuan   

  1. Department of Chemistry, The SEDC Research Laboratory of AnalyticalScience for Material and Life Chemistry, Xiamen University, Xiamen, 361005
  • Received:1996-07-03 Online:1997-06-24 Published:1997-06-24

关键词: 人工神经元网络, 偏最小二乘法, 传感器阵列, 建模

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

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