Calculation method for mining subsidence combining probability integral method and SBAS-InSAR

To address the issues of local optima and inaccurate edge subsidence predictions in the parameter inversion process of the mining subsidence probability integral method, the authors propose applying the dung beetle optimizer algorithm to invert probability integral method parameters and integrate SB...

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Main Authors: DING Xingcheng, LI Peixian, KANG Xinliang, WANG Mingliang, ZHANG Tao, HAO Dengcheng
Format: Article
Language:English
Published: Emergency Management Press 2025-02-01
Series:矿业科学学报
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Online Access:http://kykxxb.cumtb.edu.cn/en/article/doi/10.19606/j.cnki.jmst.2024938
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author DING Xingcheng
LI Peixian
KANG Xinliang
WANG Mingliang
ZHANG Tao
HAO Dengcheng
author_facet DING Xingcheng
LI Peixian
KANG Xinliang
WANG Mingliang
ZHANG Tao
HAO Dengcheng
author_sort DING Xingcheng
collection DOAJ
description To address the issues of local optima and inaccurate edge subsidence predictions in the parameter inversion process of the mining subsidence probability integral method, the authors propose applying the dung beetle optimizer algorithm to invert probability integral method parameters and integrate SBAS-InSAR subsidence monitoring values to obtain comprehensive subsidence information for the mining area. The method first utilizes gradient information from SBAS-InSAR technology to obtain reliable subsidence values for areas with small deformation gradients in the mining area. It then applies to the dung beetle optimizer algorithm, known for its strong optimization capability and high accuracy, to invert the parameters of the probability integral method and calculate subsidence values for areas with large deformation gradients. Finally, the subsidence values from the probability integral method and SBAS-InSAR monitoring are fused using a quadratic distance weighting method approach to derive the mining subsidence deformation information for the mining area. Using the 10604 working face of the Malan Mine in Gujiao City, Shanxi Province, as the study area, experimental analysis was conducted using data from 62 field leveling monitoring points and 25 Sentinel-1A images. The results indicate that the parameter inversion using the dung beetle optimizer algorithm is excellent, and accurate subsidence information can be obtained after data fusion. This approach improves accuracy by 59 % compared to using SBAS-InSAR alone and by 32 % compared to using the probability integral method alone.
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spelling doaj-art-b87ee951552b4aa6810b0ed5f66b79a32025-08-20T02:56:03ZengEmergency Management Press矿业科学学报2096-21932025-02-01101485610.19606/j.cnki.jmst.2024938kykxxb-10-1-48Calculation method for mining subsidence combining probability integral method and SBAS-InSARDING Xingcheng0LI Peixian1KANG Xinliang2WANG Mingliang3ZHANG Tao4HAO Dengcheng5College of Geoscience and Surveying Engineering, China University of Mining and Technology-Beijing, Beijing 100083, ChinaCollege of Geoscience and Surveying Engineering, China University of Mining and Technology-Beijing, Beijing 100083, ChinaGeological Department, XiShan Coal Electricity Group Co., Ltd., Taiyuan Shanxi 030053, ChinaCollege of Geoscience and Surveying Engineering, China University of Mining and Technology-Beijing, Beijing 100083, ChinaCollege of Geoscience and Surveying Engineering, China University of Mining and Technology-Beijing, Beijing 100083, ChinaChina Centre for Resources Satellite Data and Application, Beijing 100094, ChinaTo address the issues of local optima and inaccurate edge subsidence predictions in the parameter inversion process of the mining subsidence probability integral method, the authors propose applying the dung beetle optimizer algorithm to invert probability integral method parameters and integrate SBAS-InSAR subsidence monitoring values to obtain comprehensive subsidence information for the mining area. The method first utilizes gradient information from SBAS-InSAR technology to obtain reliable subsidence values for areas with small deformation gradients in the mining area. It then applies to the dung beetle optimizer algorithm, known for its strong optimization capability and high accuracy, to invert the parameters of the probability integral method and calculate subsidence values for areas with large deformation gradients. Finally, the subsidence values from the probability integral method and SBAS-InSAR monitoring are fused using a quadratic distance weighting method approach to derive the mining subsidence deformation information for the mining area. Using the 10604 working face of the Malan Mine in Gujiao City, Shanxi Province, as the study area, experimental analysis was conducted using data from 62 field leveling monitoring points and 25 Sentinel-1A images. The results indicate that the parameter inversion using the dung beetle optimizer algorithm is excellent, and accurate subsidence information can be obtained after data fusion. This approach improves accuracy by 59 % compared to using SBAS-InSAR alone and by 32 % compared to using the probability integral method alone.http://kykxxb.cumtb.edu.cn/en/article/doi/10.19606/j.cnki.jmst.2024938mining subsidenceprobability integral methoddung beetle optimizer algorithmsbas-insardata fusion
spellingShingle DING Xingcheng
LI Peixian
KANG Xinliang
WANG Mingliang
ZHANG Tao
HAO Dengcheng
Calculation method for mining subsidence combining probability integral method and SBAS-InSAR
矿业科学学报
mining subsidence
probability integral method
dung beetle optimizer algorithm
sbas-insar
data fusion
title Calculation method for mining subsidence combining probability integral method and SBAS-InSAR
title_full Calculation method for mining subsidence combining probability integral method and SBAS-InSAR
title_fullStr Calculation method for mining subsidence combining probability integral method and SBAS-InSAR
title_full_unstemmed Calculation method for mining subsidence combining probability integral method and SBAS-InSAR
title_short Calculation method for mining subsidence combining probability integral method and SBAS-InSAR
title_sort calculation method for mining subsidence combining probability integral method and sbas insar
topic mining subsidence
probability integral method
dung beetle optimizer algorithm
sbas-insar
data fusion
url http://kykxxb.cumtb.edu.cn/en/article/doi/10.19606/j.cnki.jmst.2024938
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