Multi-source information fusion and stability prediction of slope based on gradient boosting decision tree

Accurate prediction of slope stability is very important to reduce the frequency of landslides and the cost of slope maintenance. For rock slope engineering, there will be new cracks or old cracks inside the engineering rock mass in the process of disaster development. With the development of the internal fracture of rock mass, the physical parameters of rock mass will change constantly, therefor it has become an important method to predict the stability of rock slope by monitoring the changes of physical parameters of rock mass. However, the traditional single monitoring information can directly reflect the landslide trend, but it has the characteristics of locality and delay, and cannot completely reflect the state of the slope. Based on the three heterogeneous information including micro-seismic, stress and displacement, this paper puts forward a method of using multi-source monitoring information fusion technology to predict and analyze the slope stability. According to the actual geological conditions of Dagushan open pit mine slope, the change rule of monitoring information in different states of slope is obtained by the finite element strength reduction method, the GBDT method is used to integrate the monitoring information, and the nonlinear model of slope stability prediction is established. The conclusions are as follows: ① the combination of the GBDT method and the finite element strength reduction method can realize the fusion of heterogeneous information such as displacement, stress and micro-seismic of the slope, and the monitoring data in the actual slope of Dagushan Iron Mine is used to verify the effectiveness of the proposed method; ② compared with other fusion algorithms, the GBDT model has superior performance in prediction accuracy and model interpretation ability. The model can identify complex nonlinear relations well, and is suitable for the prediction of slope safety in the open pit mine; ③ based on the GBDT algorithm, it can calculate the weight of different monitoring information for slope safety. The study shows that the displacement change of the slope top and the number of microseisms inside the slope play a leading role in the stability prediction of the slope. © 2020, Editorial Office of Journal of China Coal Society. All right reserved.