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 peri odic operation in our previous paper. in this paper, we propose fuzzy rule- based neural networks, which are composed of two back propagation neural ne tworks, to improve the estimation accuracy and to reduce the time and effor ts for creation and tuning of the membership functions. The proposed networ k is examined in estimating the concentrations of three kinds of inflammabl e gases, that is, butane, hydrogen and methane, and it is proved that the r esults are more accurate than those obtained with simplified fuzzy inferenc e. (C) 1999 Elsevier Science S.A. All rights reserved.