  In order to better model complex real-world data such as multiphase flow, one
approach is to develop pattern recognition techniques and robust features that
capture the relevant information. In this paper, we use deep learning methods,
and in particular employ the multilayer perceptron, to build an algorithm that
can predict flow pattern in twophase flow from fluid properties and pipe
conditions. The preliminary results show excellent performance when compared
with classical methods of flow pattern prediction.
