根据边坡位移监测信息，应用灰色系统原理和方法，建立GM(1,1)模型，模拟边坡位移并预测其发展趋势。
Based on the materials of a practical survey on the displacement of a slope the gray model GM (1, 1) is established in the paper to reproduce the displacement and predict its development trend.
现场监测发现，边坡位移随时间起伏变化，怀疑其影响因素之一可能是气温变化。
According to in-situ monitoring data, the displacement of rock slope varies with time, and the variation of air temperature is doubted to be one of the influencing factors.
选择边坡内某些监测点的位移突变特征作为强度折减法的材料破坏判据。
The displacement mutation characteristics of monitoring points were chosen as the failure criteria of materials in the shear strength reduction method.
钻孔测斜仪是一种测定钻孔横向位移的原位监测仪器，在边坡工程原位监测中应用最为广泛。
Borehole inclinometer is a monitoring instrument in situ to measure lateral displacement of borehole. It is extensively used in slope engineering.
其内容包括“MBJ—1边坡无线监测仪”及“MW—1霍尔效应双向数字式位移传感器”两部分。
MBJ-1 wireless slope monitor and MW-1 Hall Effect Duplex Digital Displacement Transducer.
讨论了岩质边坡位移可视化分析涉及的若干技术，介绍了该项研究的工程背景及现场监测网络的情况，重点就可视化分析系统展开论述。
Some techniques for visual of rock slope were discussed. The authors introduced the background and field monitoring network of the project, with an emphasis on describing its visual analysis system.
同时监测结果表明，降雨和开挖使边坡位移速率显著增大。
The influence of rainfall and excavation on slope displacement is proven immediately by increasing slope deformation rate.
并根据边坡地面和地下监测资料，对边坡的变形特点、岩体的变形特征与破坏模式进行了详细的研究，分析了这类边坡地表和深部位移变化规律。
According to the obtained data, the deformation feature of rock body and the damage pattern of the slope have been discussed in detail. Finally, the rules of slope deformation are given.
边坡系统是一类典型的复杂灰色系统，由于其位移监测数据离散程度较高，因此应用经典灰色预测模型往往会出现预测值偏差较大的情况。
Slope system is a sort of typical complex gray system, applying classical gray prediction model will engender large error in predicted value due to the high discrete degree of monitored displacement.
边坡系统是一类典型的复杂灰色系统，由于其位移监测数据离散程度较高，因此应用经典灰色预测模型往往会出现预测值偏差较大的情况。
Slope system is a sort of typical complex gray system, applying classical gray prediction model will engender large error in predicted value due to the high discrete degree of monitored displacement.
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