A New Method Using Artificial Neural Networks to Group Mines into Similar Sets for Efficient Management and Transformation

Author:

Wyganowska Małgorzata1ORCID,Bańka Piotr2ORCID

Affiliation:

1. Department of Safety Engineering, Faculty of Mining, Safety Engineering and Industrial Automation, Silesian University of Technology, 44-100 Gliwice, Poland

2. Department of Geoengineering and Raw Materials Extraction, Faculty of Mining, Safety Engineering and Industrial Automation, Silesian University of Technology, 44-100 Gliwice, Poland

Abstract

The market economy means that only those companies that are characterised by the generation of positive economic results and liquidity can function, survive and thrive. Due to the importance of the coal industry in economic and social terms—due to the number of people employed in the coal industry—it is necessary to constantly search for methods to improve management and business efficiency. This paper proposes the use of artificial neural networks to group mines into sets of similar mines. These sets can be used to make different business decisions for these companies. These sites can be easily compared with each other, in search of the areas that need to be restructured. In addition, developing pro-efficiency strategies for designated groups of similar mines is simpler than for each mine individually. This reduces the number of such studies in real terms and allows effective business measures to be applied more quickly.

Funder

Faculty of Mining, Safety Engineering and Industrial Automation, Silesian University of Technology, Poland

Publisher

MDPI AG

Reference33 articles.

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4. Kaufmann, A., and Faure, R. (1968). Badania Operacyjne na co Dzień, PWN.

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