Research on intelligent prediction and experiment of coal moisture content in port yard based on EMD-GRU
Aiming at the demand of watering and dust suppression in coal port yard,a prediction model of coal moisture content based on EMD-GRU was put forward,and experimental verification was carried out.By establishing the prediction model of coal moisture content in the storage yard,using real-time data-driven to predict the change of moisture content in the coal stack,the future dust generation of the coal stack could be determined according to the meteorological data and the change of moisture content,and the corresponding watering strategy was formulated.The experimental results showed that the root mean square error,average absolute error,average absolute percentage error and determination coefficient of the EMD-GRU model proposed in this paper were 0.768,0.566,9.52％and 0.944 respectively.Compared with SVR,DTR,RNN,LSTM,GRU and other prediction models,EMD-GRU prediction model had the lowest error values,the highest determination coefficient,and the best prediction accuracy and fitting effect.
coal moisture contentmeteorological elementsdeep learningEMD-GRUprediction model
NETL
NSTL
万方数据
