{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T14:09:50Z","timestamp":1777385390722,"version":"3.51.4"},"reference-count":38,"publisher":"Wiley","license":[{"start":{"date-parts":[[2020,11,3]],"date-time":"2020-11-03T00:00:00Z","timestamp":1604361600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41874012"],"award-info":[{"award-number":["41874012"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41674013"],"award-info":[{"award-number":["41674013"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Journal of Sensors"],"published-print":{"date-parts":[[2020,11,3]]},"abstract":"<jats:p>Given the increasingly serious geological disasters caused by underground mining in the Hancheng mining area in China and the existing problems with mining subsidence prediction models, this article uses the small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) technology to process 109 Sentinel-1A images of this mining area from December 2015 to February 2020. The results show that there are three subsidences: one in Donganshang, one in south of Zhuyuan village, and one in Shandizhaizi village. In the basin, the maximum annual average subsidence rate is 300\u2009mm\/a, and the maximum cumulative subsidence is 1000\u2009mm. The SBAS-InSAR results are compared with Global Positioning System (GPS) observation results, and the correlation coefficient is 74%. Finally, a simulated annealing (SA) algorithm is used to estimate the optimal parameters of a support vector regression (SVR) prediction model, which is applied for mining subsidence prediction. The prediction results are compared with the results of SVR and the GM (1, 1). The minimum value of the coefficient of determination for prediction with SA-SVR model is 0.57, which is significantly better than that those of the other two prediction methods. The results indicate that the proposed prediction model offers high subsidence prediction accuracy and fully meets the requirements of engineering applications.<\/jats:p>","DOI":"10.1155\/2020\/8860225","type":"journal-article","created":{"date-parts":[[2020,11,5]],"date-time":"2020-11-05T02:35:20Z","timestamp":1604543720000},"page":"1-17","source":"Crossref","is-referenced-by-count":11,"title":["On Time-Series InSAR by SA-SVR Algorithm: Prediction and Analysis of Mining Subsidence"],"prefix":"10.1155","volume":"2020","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7017-1505","authenticated-orcid":true,"given":"Yun","family":"Shi","sequence":"first","affiliation":[{"name":"School of Geomatics, Xi\u2019an University of Science and Technology, Xi\u2019an, Shaanxi 710054, China"},{"name":"Key Laboratory of Coal Resources Exploration and Comprehensive Utilization, Ministry of Natural Resources, Xi\u2019an, Shaanxi 710021, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qianwen","family":"Li","sequence":"additional","affiliation":[{"name":"School of Geomatics, Xi\u2019an University of Science and Technology, Xi\u2019an, Shaanxi 710054, China"},{"name":"Key Laboratory of Coal Resources Exploration and Comprehensive Utilization, Ministry of Natural Resources, Xi\u2019an, Shaanxi 710021, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Meng","sequence":"additional","affiliation":[{"name":"Xi\u2019an Research Institute of Surveying and Mapping, Xi\u2019an 710054, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tongkang","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Geomatics, Xi\u2019an University of Science and Technology, Xi\u2019an, Shaanxi 710054, China"},{"name":"Key Laboratory of Coal Resources Exploration and Comprehensive Utilization, Ministry of Natural Resources, Xi\u2019an, Shaanxi 710021, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5230-2209","authenticated-orcid":true,"given":"Jingjian","family":"Shi","sequence":"additional","affiliation":[{"name":"School of Geomatics, Xi\u2019an University of Science and Technology, Xi\u2019an, Shaanxi 710054, China"},{"name":"Key Laboratory of Coal Resources Exploration and Comprehensive Utilization, Ministry of Natural Resources, Xi\u2019an, Shaanxi 710021, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"1","volume-title":"Mining Subsidence","author":"G. 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