Fast detection of hazardous organic gases in the ambient air using adaptive neuro-fuzzy inference systems

In this study, an adaptive neuro-fuzzy inference system (ANFIS) is proposed for the concentration estimation of volatile organic gases before the sensor response time by using the transient sensor response. A neural network (NN) structure with tapped time delays and Mamdani's fuzzy inference system (FIS) are also used for comparison. The estimation results of ANFIS are better than those of the Mamdani's FIS and much closer to those of the NN. Acceptable performance is obtained for all systems, and the appropriateness of ANFIS for the gas-concentration determination before the sensor response time is observed.