Prediction of Selected Production Goals by Classification Methods

Abstract:

The goal of this work was to use the process of knowledge discovery in planning and control of production processes. This work is focused on the prediction of the system behavior from the data of production process. The classification was used as a task of data mining. Some predictive models were created and the predictions of the production process behavior were realized by varying the input parameters using selected methods and techniques of data mining. It can be confirmed that the selected input parameters will lead to the fulfillment of the declared objectives of the process. The process of knowledge discovery has been implemented in the program STATISTICA Data Miner.

• Periodical: Applied Mechanics and Materials (Volume 474)
• Pages: 115-120
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.474.115
• Online since: January 2014
• Authors: Dominika Jurovatá, Pavel Važan, Michal Kebisek, Pavol Tanuska, Lukáš Hrčka
• Keywords: CRISP-DM, Data Mining (DM), Neural Network (NN), Prediction, Production

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DOI: 10.1002/9781119019855

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