煤矿安全2025，Vol.56Issue(4)：146-154,9.DOI:10.13347/j.cnki.mkaq.20231482
融合动态概率积分法模型和Logistic模型的地表采煤沉陷动态预测方法
A dynamic prediction method for surface mining subsidence based on dynamic probability integral model and Logistic model
摘要
Abstract
In order to accurately describe the dynamic evolution of surface deformation over time caused by underground coal min-ing,a dynamic probability integral method model(DPIM)was first constructed by combining the probability integral method model(PIM)and the Knothe time function model.Then,taking into account the changing rules of the predicted parameters during mining process,the Logistic model was used to fit the dynamic predicted parameters,and a DPIM-Logistic dynamic fusion subsidence pre-diction model was constructed.Finally,in view of the highly nonlinear function of the predicted model,the fireworks algorithm was introduced to solve the parameters of the model.Simulation experiments show that the error in subsidence fitting is 2.37 mm and the error in prediction results is 5.74 mm in inverting parameters.This method was applied to a working face in Huainan Mining Area.The error in the inversion parameter fitting was 59.67 mm,and the error in the prediction results was 73.10 mm.It effectively veri-fied the accuracy and reliability of the predicted results.关键词
地表形变/采煤沉陷/地表沉陷动态预测/概率积分法/Knothe时间函数/Logistic模型/烟花算法Key words
surface deformation/mining subsidence/dynamic prediction of surface subsidence/probability integral method/Knothe time function/Logistic model/fireworks algorithm分类
矿业与冶金引用本文复制引用
韩磊,戚鑫鑫,王天君,裴春敏,王旭东..融合动态概率积分法模型和Logistic模型的地表采煤沉陷动态预测方法[J].煤矿安全,2025,56(4):146-154,9.基金项目
安徽省优秀青年科学基金资助项目(2108085Y20) （2108085Y20）
