ARRANGEMENT FOR MODELING A NON-LINEAR PROCESS

An arrangement for modeling a non-linear process including at least one input variable (x1, x2) and at least one output variable (y) can include a neural network and a device for specifying functional (or operational) values. A function of the neural network is determined in a first part of the domain of input variables (x1, x2) by learning from measuring data, which are obtained from the process by acquiring measured values. An empirically based device for specifying functional (or operational) values, preferably a fuzzy system, is provided in a second part of the domain of input variables (x1, x2) in which there are no measuring data for training the neural network. This arrangement is particularly useful when it is implemented in controllers.