  In that paper we discuss possibilities of using the Artificial Neural Network
technic for the individual Extensive Air Showers data evaluation. It is shown
that the recently developed new computational methods can be used in studies of
EAS registered by very large and complex detector systems. The ANN can be used
to classify showers due to e.g. primary particle mass as well as to find a
particular EAS parameter like e.g. total muon number. The examples of both
kinds of analysis are given and discussed.

High Energy Physics - Phenomenology