Forecasting the Friction Factor of a Mine Airway Using an Improvement Stacking Ensemble Learning Approach
Zhipeng Qi,
Ke Gao,
Dariusz Obracaj
et al.
Abstract:The prediction of frictional air resistance using the inherent properties of roadways is of great significance for ventilation network computation and flow regulation in underground mines. This study proposes an improved stacked learning and error correction-based prediction model for the frictional air resistance of mine airways, called friction factor. A prediction set is established by selecting ten factors, including tunnel spatial features and support forms, with the ventilation resistance coefficient as … Show more
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