Problem identification also contains analysis of the present problem awareness. The problem knowledge may contain data and rules. If data are available, the independent variables (the input variables) should be clearly distinguished from the highly dependent variables (the output variables) in order to choose a proper neural network architecture and a learning method. These variables can be discrete, continuous, linguistic, boolean, etc.