摘要
针对邵东县城及周边地区石膏矿采空区地面变形频发,选取8个典型矿山,运用基于神经网络的石膏矿采空区稳定性评价方法,建立以覆盖层情况、顶板情况、地质构造复杂程度、矿层倾角、开采深度、开采厚度、矿柱留设情况等7个指标为参数的采空区稳定性评价神经网络模型,对矿山进行采空区稳定性评价,根据评价结果提出了相应的防治建议。评价结果与现场实际情况吻合较好,表明该评价方法可推广应用于类似的石膏矿采空区稳定性评价。
The ground deformation of gypsum mine gob in Shaodong County and surrounding areas take place frequently. The paper select 8 typical mines, using gypsum mine gob stability evaluation method based on neural network, and then establish a gob stability evaluation neural network model with 7 indicators, such as covering, roof, complex geological structure, seam inclination and degree mining depth, mining thickness, pillar set-up. Therefore the paper evaluates the stability of mine gob area and give correspond suggestion based on the evaluation results. The evaluation results are in good agreement with the actual situation of the site, indicating that the evaluation method can be applied to evaluate the stability of similar gypsum mine
出处
《国土资源导刊》
2017年第3期70-75,共6页
Land & Resources Herald
关键词
采空区
地面变形
稳定性
神经网络
mined out area
ground deformation
stability
neural network
