This article presents the results of research concerning
possibilities of applying multilayer perceptron type of neural
network for fault diagnosis, state estimation, and prediction
in the gas pipeline transmission network. The influence of several
factors on accuracy of the multilayer perceptron was considered.
The emphasis was put on the multilayer perceptrons' function
as a state estimator. The choice of the most informative features,
the amount and sampling period of training data sets, as well
as different configurations of multilayer perceptrons were analyzed.