AAIA’16 Data Mining Challenge
AAIA'16 Data Mining Competition:
AAIA'16 Data Mining Challenge was the third data mining competition associated with International Symposium on Advances in Artificial Intelligence and Applications (AAIA'16) which is a part of FedCSIS conference series. This time, the task was related to the problem of predicting periods of increased seismic activity which may cause life-threatening accidents in underground coal mines. Prizes worth over 3,000 USD were awarded to the most successful teams. The contest is sponsored by Research and Development Centre EMAG with support from Polish Information Processing Society and Dituel Sp. z o.o..
- Michal Tadeusiak (team tadeusz) from Deepsense.io, Poland - "Early Warning System for Seismic Events in Coal Mines Using Machine Learning"
- Robert Bogucki, Jan Lasek, Jan Kanty Milczek, Michał Tadeusiak (team deepsense.io from Deepsense.io, Poland - "Early Warning System for Seismic Events in Coal Mines Using Machine Learning"
- Yasser Tabandeh (team yata) from Golgohar Mining & Industrial Company, Iran
- Marc Boullé - "Predicting Dangerous Seismic Events in Coal Mines under Distribution Drift"
- Marek Grzegorzewski - "Massively Parallel Feature Extraction Framework Application in Predicting Dangerous Seismic Events"
- Başak Esin Köktürk Güzel and Bilge Karaçalı - "Fisher’s Linear Discriminant Analysis Based Prediction using Transient Features of Seismic Events in Coal Mines"
- Łukasz Podlodowski - "Utilizing an ensemble of SVMs with GMM voting-based mechanism in predicting dangerous seismic events in active coal mines"
- Karol Kurach, Krzysztof Pawłowski - "Predicting Dangerous Seismic Activity with Recurrent Neural Networks"
- Eftim Zdravevski, Petre Lameski, Andrea Kulakov - "Automatic Feature Engineering for Prediction of Dangerous Seismic Activities in Coal Mines"
- Marcin Michalak, Katarzyna Dusza, Dominik Korda, Krzysztof Kozłowski, Bartlomiej Szwej, Michał Kozielski, Marek Sikora, Łukasz Wróbel - "Application of RapidMiner and R Environments to Dangerous Seismic Events Prediction"