Window-Based Feature Engineering for Prediction of Methane Threats in Coal Mines
We present our results of experiments concerning the methane threats prediction in coal mines obtained during IJCRS’15 Data Challenge. The data mining competition task poses the problem of active monitoring and early threats detection which is essential to prevent spontaneous gas explosions. This issue is very important for the safety of people and equipment as well as minimization of production losses. The discussed research was conducted also to verify the effectiveness of the feature engineering framework developed in the DISESOR project. The utilized framework is based on a sliding window approach and is designed to handle numerous streams of sensor readings.
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