The application of fuzzy-neural network algorithm on the estimation of inflammable gas concentration

Author

Yea, Byeongdeok ; Osaki, Tomoyuki ; Sugahara, Kazunori ; Konishi, Ryosuke

Author_Institution

Dept. of Electr. & Electron. Eng., Tottori Univ., Japan

fYear

1997

fDate

29-31 Jul 1997

Firstpage

941

Lastpage

946

Abstract

This paper describes the application of a fuzzy-neural network on the concentration-estimation of inflammable gases. Not only the membership functions for premises and consequences of fuzzy if-then rules are created and adjusted automatically but also the concentrations of the inflammable gases introduced are calculated automatically with the fuzzy-neural network. The proposed method is examined in estimating the concentrations of three kinds of inflammable gases, that is, hydrogen, butane and methane, and it is proved that the results are more accurate than those obtained with fuzzy inference

Keywords

chemical engineering computing; chemical variables measurement; chemistry computing; computerised instrumentation; fuzzy neural nets; gas sensors; H₂; butane; fuzzy if-then rules; fuzzy inference; fuzzy-neural network algorithm; hydrogen; inflammable gas concentration estimation; methane; Artificial neural networks; Conducting materials; Electronic mail; Flammability; Fuzzy neural networks; Gas detectors; Gases; Hydrogen; Neural networks; Zinc oxide;

fLanguage

English

Publisher

ieee

Conference_Titel

SICE '97. Proceedings of the 36th SICE Annual Conference. International Session Papers

Conference_Location

Tokushima

Type

conf

DOI

10.1109/SICE.1997.624883

Filename

624883