黑龙江科技大学学报2024，Vol.34Issue(3)：360-366,7.DOI:10.3969/j.issn.2095-7262.2024.03.005
M-CM-GA-BP算法的地表移动变形参数预测模型
Prediction model of surface movement and deformation paramete based on M-CM-GA-BP algorith
摘要
Abstract
This paper aims to address the complex mining subsidence prediction problem and propo-ses a prediction model based on M-CM-GA-BP algorithm to obtain surface movement and deformation pa-rameters by studying the variation law behind surface movement and deformation parameters at 22 working faces.The study includes optimizing the weights and thresholds of BP neural network by linear weighted combination prediction method and genetic algorithm;integrating the multiple linear regression model to improve the accuracy of surface movement and deformation parameters;analyzing the prediction perform-ance of the model compared with other prediction models,and to verify the accuracy of the model.The results show that this model can effectively improve the prediction accuracy of surface movement and de-formation parameters.The parameters with average relative error by 1.294 and the root mean square error by 0.013 provide a feasible method for the prediction of surface movement and deformation parameters.关键词
开采沉陷/BP神经网络/地表移动变形参数/组合模型/参数预测Key words
mining subsidence/BP neural network/surface movement deformation parameters/combination model/parameter prediction分类
矿业与冶金引用本文复制引用
秦忠诚,高广慧,李晓禾,席天乐..M-CM-GA-BP算法的地表移动变形参数预测模型[J].黑龙江科技大学学报,2024,34(3):360-366,7.基金项目
山东省自然科学基金面上项目(ZR2021ME248) （ZR2021ME248）
山东省自然科学基金重点项目(ZR2020KE030) （ZR2020KE030）
