Improvement of concentration-estimation algorithm for inflammable gases utilizing fuzzy rule-based neural networks

We have proposed an algorithm which can discriminate inflammable gases and estimate their concentration with a semiconductor gas sensor under the periodic operation in our previous paper. in this paper, we propose fuzzy rule-based neural networks, which are composed of two back propagation neural networks, to improve the estimation accuracy and to reduce the time and efforts for creation and tuning of the membership functions. The proposed network is examined in estimating the concentrations of three kinds of inflammable gases, that is, butane, hydrogen and methane, and it is proved that the results are more accurate than those obtained with simplified fuzzy inference. (C) 1999 Elsevier Science S.A. All rights reserved.