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基于时间序列AR(P)模型的边坡变形预测与应用

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获取边坡的监测数据进行分析,并预测其接下来的变化趋势,具有重要的意义.本文以贵州省福泉市高坪矿区英坪矿段内边坡工程项目为研究对象,对监测数据采用时间序列AR(P)模型方法进行了分析与预测.研究结果表明,模型拟合的结果和预测精度较好地反映了监测点的变化趋势,可为矿区边坡模型建立和监测数据的预测提供一定的参考.
Prediction and Application of Slope Deformation Based on Time-series AR (P) Model
It is of great significance to obtain the monitoring data of slope for analyzing and predicting its next change trend. Taking the slope engineering project in Yingping section of Gaoping mining area in Fuquan city, Guizhou province as the research object, this pa-per analyzes and forecasts the monitoring data by using the time series AR (P) model method. The results show that the fitting results and prediction accuracy of the model can better reflect the change trend of monitoring points, and can provide a certain reference for the establishment of slope model and the prediction of monitoring data in mining area.

mine slopedeformation monitoringtime-series AR (P) modelprediction

陈子江

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贵州地矿基础工程有限公司, 贵州贵阳 550081

贵州省地矿局地球物理地球化学勘查院, 贵州贵阳 550018

矿区边坡 变形监测 时间序列AR(P)模型 预测

2024

测绘与空间地理信息
黑龙江省测绘学会

测绘与空间地理信息

影响因子:0.788
ISSN:1672-5867
年,卷(期):2024.47(7)
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