湖北农业科学 ›› 2020, Vol. 59 ›› Issue (21): 69-74.doi: 10.14088/j.cnki.issn0439-8114.2020.21.014

• 资源·环境 • 上一篇    下一篇

基于R/S分析及极限学习机的沉陷区土地复垦适宜性研究

陈强, 黄鑫, 拉换才让   

  1. 青海省水文地质及地热地质重点实验室/青海省水文地质工程地质环境地质调查院,西宁 810008
  • 收稿日期:2020-01-10 出版日期:2020-11-10 发布日期:2020-12-21
  • 作者简介:陈 强(1985-),男,陕西薄城人,工程师,主要从事水文地质、工程地质和环境地质研究,(电话)13666182073(电子信箱)193334045@qq.com。

Study on the suitability of land reclamation in subsidence area based on R/S analysis and limit learning machine

CHEN Qiang, HUANG Xin, Lahuancairang   

  1. Qinghai Key Laboratory of Hydrogeology and Geothermal Geology/Qinghai Institute of Hydro Geology, Engineering Geology and Enviromental Geology Survey, Xining 810008, China
  • Received:2020-01-10 Online:2020-11-10 Published:2020-12-21

摘要: 为解决采煤沉陷引发的土地破坏问题,达到保持矿区生态环境稳定的目的,以R/S分析及极限学习机为理论基础,开展沉陷区土地复垦的适宜性研究。首先,利用R/S分析对沉陷区的稳定性现状进行判断,并分析沉陷稳定性随时间的演化规律,再利用极限学习机构建沉陷变形预测模型,以评价沉陷变形的发展趋势,进而为土地复垦提供依据;最后,结合采煤沉陷特点,开展沉陷区的土地复垦措施研究。实例分析表明,R/S分析能有效评价沉陷区的沉陷稳定性,得出不同阶段的沉陷稳定性存在一定差异,但大致呈随时间持续稳定性增加的趋势;同时,通过沉陷变形预测,得出该预测模型预测结果的相对误差均值小于3%,具有较高的预测精度,表明该预测模型在沉陷区变形预测中的适用性,且后期沉陷变形趋于稳定,并与稳定性评价综合得出后续适宜采取的土地复垦措施。沉陷区土地复垦是一个系统工作且势在必行,应通过沉陷稳定性评价掌握合理的复垦时机,并结合矿区的复垦条件,合理规范复垦措施,提高土地利用率。

关键词: 采煤沉陷区, R/S分析, 极限学习机, 稳定性评价, 土地复垦

Abstract: In order to solve the problem of land destruction caused by mining subsidence and to maintain the ecological environment stability of the mining area, the study on the suitability of land reclamation in subsidence area was carried out based on the theory of R/S analysis and limit learning machine. Firstly, the stability status of subsidence area was judged by R/S analysis, and the evolution law of subsidence stability with time was analyzed. Then, the prediction model of subsidence deformation was built by using limit learning machine to evaluate the development trend of subsidence deformation, so as to provide basis for land reclamation. Finally, the study on land reclamation measures in the subsidence area was carried out combined with the characteristics of coal mining subsidence. The case study showed that the R/S analysis could effectively evaluate the subsidence stability of the subsidence area, and that there were some differences in the subsidence stability of different stages, but the stability tended to increase with time. At the same time, through the prediction of subsidence deformation, the relative error mean value of the prediction results of the prediction model was less than 3%, which has high prediction accuracy, and the prediction model was verified. The subsidence deformation tended to be stable in the later period, and the stability evaluation was integrated to obtain the appropriate land reclamation measures to be taken in the future. Finally, the land reclamation in the subsidence area is a systematic work, and it is imperative to grasp the reasonable reclamation opportunity through the settlement stability evaluation, and reasonably standardize the reclamation measures in combination with the reclamation conditions of the mining area, to improve land use efficiency.

Key words: mining subsidence area, R/S analysis, limit learning machine, stability evaluation, land reclamation

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