Research on the application of T-S fuzzy neural network in quantitative identification of mixed gas

Abstract

This article integrated rule expression capacity of fuzzy logic inference with self-learning ability of the neural network, proposed to build Takagi-Sugeno fuzzy neural network's quantitative identification of mixed gas by combining T-S fuzzy neural network with neural network. The results indicated that this system has generalization, learning, mapping capabilities. It can better realize quantitative identification of mixed gas. This system will provide method for intelligent identification of mixed gas. © 2013 Springer-Verlag.