## 4 Case Study
This tensile stress concentration results in the tensile fracture and dislocation deformation of the rock and soil mass towards the free face, thereby forming transverse tensile cracks. Figure 4:1 Deformation velocity curve and deformation velocity confidence interval. Figure 4:2 Displacement, v-SMA, and v-LMA curve. that the actual landslide time can be accurately predicted 4 h in advance, and there is no lag in the prediction time. We adopted the method proposed by [PERSON], which involves the intersection of the short-term moving average line and the long-term moving average line, to calculate the starting point OOA of the acceleration stage. Meanwhile, the landslide time was predicted by applying the reciprocal velocity method. The analysis results regarding the predicted landslide time and the actual landslide time are presented in Figure 4:3 \begin{table}
\begin{tabular}{c c c} \hline
**OOA (t = 60.6)** & **Prediction Time/h** & **Actual Failure Time/h** \\ \hline Raw data & 96.89 & 94.74 \\ SMA & 97.91 & 94.74 \\ LMA & 100.6 & 94.74 \\ \hline \end{tabular}
\end{table} 
Table 4: Comparison of landslide time predicted by traditional methods and actual landslide time. Figure 14: Comparison curve of landslide prediction time and actual landslide time. Figure 13: Slope landslide deformation photo (the photo was taken by the author). As can be observed from the table, when utilizing the OOA point, the short-term moving average (SMA), and the long-term moving average (LMA) to predict the landslide time, a time lag in the predicted time occurred. The reason for this is that the OOA point obtained through the intersection method of the short-term moving average line and the long-term moving average line is actually earlier than the starting moment of the real acceleration deformation stage. Consequently, the method of identifying the starting point of acceleration by employing the normal distribution confidence interval proposed in this paper proves to be more precise. The reciprocal velocity method utilizes the velocity monitoring data in the accelerated deformation stage. Its basic assumption is that the deformation velocity of the slope is infinite at the moment of sliding; that is, the intersection point of the linear trend line of the reciprocal value of velocity and time on the time axis is the landslide time. However, in reality, the velocity at the time of a landslide is not infinite, but a value between 0 and infinity. In the calculation case in this paper, the maximum deformation velocity collected using the slope radar before the landslide was 48.26 mm/h. When using the logarithmic function model to predict the landslide time, the calculation error was within 0.54 h to 10 h before the actual moment the landslide began, and the prediction error was within 0.18 h to 4 h before this moment. Overall, the error is relatively small, and the closer it is to the landslide moment, the smaller the error is. The specific data are shown in Table 5.  
The landslide early warning method proposed in this paper has a broad application foundation. Included in this, the reciprocal velocity method for predicting landslide time has been applied in both mine slopes and geological landslides of mountains in China and abroad. Moreover, the Tsp point picking method and the time logarithmic model can be popularized and applied in classic creep deformation type slope landslides.