摘要
求取精准可靠的概率积分参数在开采沉陷移动变形预测中至关重要,在非线性模型广泛应用于参数预测的背景下,开展了融合FWA和Logistic模型的概率积分动态参数预测方法(FWA-Logistic方法)。结合Logistic模型的应用情况,考虑到非线性最小二乘求取模型参数的波动性较大,且不合理的初值选取会导致求参结果发散,因此引入了一种FWA算法;综合FWA算法原理、Logistic模型和概率积分动态参数变化规律,提出了FWA-Logistic方法。试验结果表明,拟合样本参数q、tanβ、θ的效果较好,拟合中误差分别为0.028、0.100和0.023°;预测各期参数q、tanβ、θ的平均相对误差分别为2.87%、2.02%、0.03%;最大相对误差约为4.39%。为验证预测参数的实用性,基于预测的各期的概率积分动态参数,代入动态概率积分模型进行地表主断面下沉预计;与实测相比,预计下沉误差在-343~208mm之间,中误差分别为47.66mm、113.60mm、86.67mm、89.23mm。
Obtaining accurate and reliable probability integral parameters is crucial in the prediction of mining subsidence movement and deformation.As the nonlinear models are widely used in parameter prediction,we developed a prediction method of probability integral dynamic parameters based on fusion of FWA and Logistic(FWA-Logistic method).Taking into account the large volatility of nonlinear least squares to obtain model parameters,and the unreasonable selection of initial values will cause the results of the parameters to diverge,an FWA algorithm was introduced.Integrating the principle of FWA algorithm,Logistic model and the law of probability integral parameter,the FWA-Logistic method was proposed.The experimental results show that the effect of fitting sample parameters q,tanβ,θwas favorable,and the RMSE in fitting were 0.028,0.100 and 0.023°,respectively;the average relative error of predicted the parameters was 2.87%,2.02%,0.03%,respectively,and the maximum relative error was 4.39%.In order to verify the practicability of the predicted parameters,based on the predicted parameters,the subsidence of the main surface section was predicted by using the dynamic probability integral model.Compared with the actual measurement,the estimated subsidence error in each period was between-343 mm and 208 mm,with the RMSE of 47.66 mm,113.60 mm,86.67 mm,89.23 mm.
作者
魏鹏
江克贵
WEI Peng;JIANG Ke-gui(Resources and Environment Administration,Shanxi Jincheng Anthracite Mining Group Co.,Ltd.,Jincheng 048006,China;School of Spatial Informatics and Geomatics Engineering,Anhui University of Science and Technology,Huainan 232001,China)
出处
《煤炭工程》
北大核心
2021年第7期123-127,共5页
Coal Engineering
基金
国家自然科学基金资助项目(52074010)。
