Neural network modelling of the gas phase of a copper flash smelting process

The paper presents the results of modelling of gaseous phase parameters of the copper flash smelting process. Models based on static and dynamic artificial neural networks are presented. The worked out models can be used for process optimisation, in turn resulting in reduction of the amount of harmful waste in the environment.