Prediction of Dust Mass Concentration in Open-Pit Mines Considering Truck Exhaust Emission Factors
Dust pollution in open-pit mines has caused serious harm to the ecological environment of mining areas and the health of employees.Accurately predicting its mass concentration plays an important guiding role in the prevention and control of air pollution.A dust mass concentration prediction model was proposed based on grey wolf optimization algorithm optimized random forest(GWO-RF).This model incorporates mining truck exhaust emission factors into the characteristic variables,with consideration of calculating the content of particulate pollutants in truck exhaust.The research results indicate that using the moving average method for noise reduction of dust mass concentration effectively improves the prediction effect.Compared with other traditional models,the GWO-RF model has the highest fitting ability and prediction accuracy.
Open-pit coal mineDust mass concentration predictionExhaust pollutionRandom forestGrey wolf optimization algorithm
万方数据
维普
