陕西煤炭2026，Vol.45Issue(3)：21-29,102,10.DOI:10.20120/j.cnki.issn.1671-749x.2026.0304
基于综放开采支架工作阻力的AGCRN矿压预测模型构建及应用
Construction and application of AGCRN strata pressure prediction model based on support working resistance in fully mechanized top coal caving mining
摘要
Abstract
In fully mechanized top coal caving(FMTCC)mining of extra-thick coal seams,traditional strata pressure predic-tion models often fail to account for the dynamic correlation of support working resistances,making it difficult to accurately characterize the strata pressure evolution law.This frequently leads to inaccurate support suitability criteria and ineffective weighting forecasts.Therefore,there is an urgent need to develop a weighting prediction model based on the dynamic correla-tion of support working resistances to achieve visual expression of the strong heterogeneity,high dynamism,and significant disturbance characteristics of strata behavior in FMTCC of extra-thick coal seams,thereby ensuring accurate and efficient weighting prediction.This study,based on the FMTCC mining of the extra-thick coal seam in Mengtai Bulian Gou Mine,pro-poses a dynamically Adaptive Graph Convolutional Recurrent Network(AGCRN)model for strata pressure prediction using deep learning and mathematical calculation methods.Through the collection,screening,and analysis of support resistance data from the No.6 coal seam,along with comparative experiments involving three types of traditional weighting prediction models,the results show that the model achieves optimal performance with an embedding dimension of 10 and a time window of 16 after hyperparameter optimization.The model's Mean Absolute Error(MAE)and Mean Absolute Percentage Error(MAPE)are as low as 551.45～601.68 and 4.49％～6.19％respectively,representing the smallest errors compared to other benchmark models and exhibiting higher accuracy and stability,which verifies the precision and superiority of the AGCRN weighting prediction model for strata pressure prediction in the extra-thick coal seam of Bulian Gou Mine.关键词
综放工作面/支架工作阻力/自适应图卷积循环网络/矿压预测/动态关联Key words
fully mechanized top coal caving face/support working resistance/adaptive graph convolutional recurrent net-work(AGCRN)/strata pressure prediction/dynamic correlation分类
矿业与冶金引用本文复制引用
张方树,牛和平,杜文刚,张玉婷,王红伟,刘朝阳..基于综放开采支架工作阻力的AGCRN矿压预测模型构建及应用[J].陕西煤炭,2026,45(3):21-29,102,10.基金项目
陕西省科技攻关计划(2024GX-YBXM-492) （2024GX-YBXM-492）
陕西省自然科学基金(2024JC-YBQN-0272) （2024JC-YBQN-0272）
