Pre-processing of the industrial data for data mining and modelling – application to the copper flash smelting process

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Pre-processing of the industrial data for data mining and modelling – application to the 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.2009.3.0261

Abstract:

The paper presents the methodology of the pre-processing of the industrial data (measurements) collected from the copper flash smelting process (Kusiak, 2009). The application of data filtering and the cleaning method for the needs of the exploratory data analysis and modelling has been discussed. The influence of the appropriate data preparation on the quality of the developed model of the considered process has also been presented.

Cite as:

Stanisławczyk, & A., Kusiak, J. (2009). Pre-processing of the industrial data for data mining and modelling – application to the copper flash smelting process. Computer Methods in Materials Science, 9(3), 369 – 373. https://doi.org/10.7494/cmms.2009.3.0261

Article (PDF):

Keywords:

Industrial data filtering, Adaptive filtering, Outlier detection

References: