A new approach to analyzing gas mixtures by transforming the problem into a pattern classification one has been proved feasible by related literature.However

when the volume fraction area of interest divides into more sub-areas or the component number of gas mixture is more than two

the number of pattern classification will increase rapidly

and cause the great increase of output nodes of ANN.This will cause not only a larger amount of computation

but also more difficultly converging to a global minimum.The numerical simulation results for a binary gas mixture indicate that a probabilistic neural network（PNN） is able to solve the problem.The PNN is easy to use

and always able to give a reasonable classification result

such as recognition rate up to 95.4 % when samples are enough.In addition

its computing load is much lighter than that of the back propagation network.