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

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

Andrzej Stanisławczyk, Jan Kusiak

AGH University of Science and Technology, Faculty of Metals Engineering,and Industrial Computer Science, Al. Mickiewicza 30, 30-059 Kraków.

DOI:

https://doi.org/10.7494/cmms.2009.3.0262

Abstract:

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.

Cite as:

Stanisławczyk, A., Kusiak, J., (2009). Neural network modelling of the gas phase of a copper flash smelting process. Computer Methods in Materials Science, 9(3), 374 – 378. https://doi.org/10.7494/cmms.2009.3.0262

Article (PDF):

Keywords:

Artificial neural networks modelling, Dynamic neural networks, Copper flash smelting process

References:

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