Abstract
A rock slope in an unstable state usually needs bolt support to avoid major disasters, but due to the complexity and uncertainty of the factor of safety (FOS) and the attributes of bolting parameters are not unified, it is not easy to acquire a satisfactory scheme. In this article, a modelling optimization method based on feedforward neural network (FNN) and particle swarm optimization (PSO) algorithm is proposed. Firstly, the process of slope bolting is simulated to obtain the FOS and an FNN model with growth mechanism is established. Secondly, the PSO algorithm is improved to realize the comprehensive consideration of discrete and continuous parameters and reduce the computational complexity with high dimensions. Finally, the accuracy of the FNN model is tested by cross-validation, and the experimental results show that the optimized bolting scheme can enhance slope stability and provide reference values for the reinforcement of slopes in actual engineering situations.
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