Predicting Dangerous Seismic Events: AAIA'16 Data Mining Challenge
Andrzej Janusz, Dominik Ślęzak, Marek Sikora, Łukasz Wróbel
DOI: http://dx.doi.org/10.15439/2016F560
Citation: Proceedings of the 2016 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 8, pages 205–211 (2016)
Abstract. This paper summarizes AAIA'16 Data Mining Challenge: Predicting Dangerous Seismic Events in Active Coal Mines which was held between October 5, 2015 and March 4, 2016 at the Knowledge Pit platform. It describes the scope and background of this competition and explains our research objectives which motivated the specific design of the competition rules. The paper also briefly overviews the results of this challenge, showing the way in which those results can help in solving practical problems related to the safety of miners working underground. In particular, our analysis focuses on applications of prediction models in order to facilitate the assessment of seismic hazards, in a situation when the exploration of a given working site has just started and there is very little historical data available.
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