Application of Sensor Fusion and Data Mining for Prediction of Methane Concentration in Coal Mines
Journal Title: Mining – Informatics, Automation and Electrical Engineering - Year 2015, Vol 524, Issue 4
Abstract
In recent years we have experienced unprecedented increase of use of sensors in many industrial applications. Modern sensors are capable of not only generating large volumes of data but as well transmit ting that data through network and storing it for further analysis. These enable to create systems capable of real-time data fusion in order to predict events of interest. The goal of this work is to predict methane concentration levels in coal mines using data fusion and data mining techniques. The paper describes an application of a generic method that can be applied to arbitrary set of multivariate time series data in order to perform classification or regression tasks. The solution presented here was developed within the framework of IJCRS‘15 data mining competition and resulted in the winning model outperforming other solutions.
Authors and Affiliations
Adam Zagorecki
Keywords
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