摘要
边坡的位移变形反映了边坡所处的稳定性状态,因而有效地预测边坡位移可以作为避灾防灾的依据,从而降低地质灾害造成的经济损失。以四川黄山石灰石矿山老鹰嘴边坡位移监测数据为样本,基于GM(1,1)模型建立了老鹰嘴边坡位移预测模型。研究表明,初始预测模型精度较低,通过残差修正,模型等级从Ⅳ级提升到Ⅱ级及以上,得到的位移预测值与实测值的变化趋势更加相近;模型预测序列长度对预测结果也具有影响,通过模型优化研究,得出模型的最佳序列长度为20。
The displacement deformation of the slope reflects the stability state of the slope,so effective prediction on the slope displacement can be used as a basis for disaster prevention,thus reducing the economic losses caused by geological disasters.Taking the displacement monitoring data of the Laoyingzui slope in Huangshan limestone mine in Sichuan as a sample,a displacement prediction model of Laoyingzui slope was established based on the GM(1,1)model.The research shows that the accuracy of the initial prediction model is low.Through residual correction,the model level is upgraded from levelⅣto levelⅡand above,and the variation trend of the obtained displacement predictive value is closer to the measured value.The prediction sequence length of the model also has an impact on the prediction results.Through model optimization research,it is concluded that the optimal sequence length for establishing the model is 20.
作者
盛建龙
张鑫
胡斌
SHENG Jianlong;ZHANG Xin;HU Bin(College of Resource and Environmental Engineering,Wuhan University of Science and Technology,Wuhan,Hubei 430081,China;Hubei Provincial Key Laboratory of Efficient Utilization and Agglomeration of Metallurgical Mineral Resources,Wuhan,Hubei 430081,China)
出处
《矿业研究与开发》
CAS
北大核心
2022年第11期82-87,共6页
Mining Research and Development
基金
国家自然科学基金重点项目(U1802243)
国家自然科学基金面上项目(41672317)
湖北省技术创新专项项目(2017ACA184)
武汉科技大学重大科技项目培育类创新团队资助项目(2018TDX01).
