Study on Dynamic Stability Prediction Model of Slope in Eastern Tibet Section of Sichuan-Tibet Highway

Abstract

The stability of the slope along the middle section of Tibet controls the safety and smoothness of the Sichuan-Tibet highway, which is affected by multiple and uncertain factors such as rainfall. The slope dynamic stability is evaluated to the benefit of that salvager can prepare in advance and preserve timely and accurately. Therefore, engineering treatment scheme in different batches, stages, and grades can be proposed prospectively. Random Forest algorithm was used to rank 10 primary factors: precipitation, earthquake, human factors, groundwater, slope height, slope gradient, dense degree, weathering depth, vegetation, and slope shape. Considering precipitation and earthquake as dynamic factors, a wavelet and NARX dynamic neural network were used to predict the trend and quantity of precipitation and earthquake, followed by developing a dynamic stability evaluation model by combining a fuzzy neural network model with other indexes. Results show that (1) the superposition error in rainfall and earthquake prediction is 0.21%, proving that the ranking of influencing factors is reasonable, and (2) the back-judgment and test accuracy of the dynamic evaluation model are 93.98% and 91.67%, respectively, indicating that the model is accurate and applicable. The model can evaluate the dynamic stability of slopes and provide more reasonable engineering protection countermeasures so that Highway Public Works Department can deal with emergencies and disasters timely and precisely.