School of Mechanics and Civil Engineering, China University of Mining and Technology-Beijing
Yunnan Institute of Water and Hydropower Engineering Investigation, Design and Research

煤巷围岩稳定控制是保障煤矿安全高效开采的关键,煤巷顶板位移量是反应煤巷围岩稳定性的关键指标,本研究提出机器学习方法对煤巷顶板位移进行超前预测研究。确定了煤巷顶板位移的8个重要影响指标,建立了煤巷顶板位移预测数据库并对数据进行了指标相关性和重要性分析。基于RF、GA-SVM和GA-ANN分别建立了三种煤巷顶板位移预测模型,选用RMSE、MAE和R2三个指标来评价模型的性能。结果显示,RF模型测试性能最佳,R2=0.909,RMSE=20.475,MAE=16.790,GA-ANN模型的性能最差。采用十折交叉方法对RF模型和GA-ANN模型进行可靠性验证,结果显示RF模型的稳定性更高,平均R2为0.891。将RF模型应用到干河煤矿2-1121巷,预测值与实际值的绝对误差为19mm,相对误差为11.18%,说明了RF模型对煤巷顶板位移预测的准确性与可靠性,研究结果对煤巷顶板位移预测提供了一种新途径。

The stability control of surrounding rocks in coal roadways is the key to ensure the safe and efficient mining of coal mine. Roof displacement is a crucial indicator to present wall rock stability. In this paper, machine learning method was introduced to predict the roof displacement of coal roadways in advance. Eight important influence indexes of roof displacement of coal roadways were defined, and the prediction database of roof dis-placement of coal roadway was established, from which the data were analyzed for correlation and importance. Based on RF, GA - SVM and GA - ANN, three roof displacement prediction models of coal roadways were estab-lished respectively, and RMSE, MAE and R2 were selected to evaluate the performance of the models. The results show that the RF model has the best performance, R2 = 0. 909, RMSE= 20. 475, MAE= 16. 790, while the GA-ANN model has the worst performance. The ten-fold cross-validation method was used to verify the reliability of RF and GA-ANN models, and it is found that RF model has higher stability, with an average R2 of 0. 891. When RF model is applied to No. 2-1121 roadway of Ganhe Coal Mine, the absolute error between the predicted and the actual value is mm, and the relative error is 11. 18%. This study shows RF model can accurately and stably predict roadway roof displacement, which provide a new reference for roadway roof displacement.

国家自然科学基金项目(52074301)

陈攀,马鑫民,向俊杰,等.基于随机森林算法的煤巷顶板位移预测与应用[J].煤炭工程,2024,56(7):127-135.