In this paper, we propose the modeling of an
industrial gas sensor “MQ-9”, where our modeling is based on
ANNs “artificial neural networks”. The gas sensor model,
obtained, operated under a dynamic environment and expresses
accurately the MQ-9 gas sensor behavior. Accordingly, it takes
into account the nonlinearity and the cross sensitivity in gas
selectivity, temperature and humidity. This model is
implemented into PSPICE “performance simulation program
with integrated circuit emphasis” simulator as an electrical
circuit in order to prove the similarity of the analytical model
output with that of the MQ-9 gas sensor.