Prediction of ground subsidence surrounding the transmission tower based on BSO-BP neural network

It is of great significance to accurately predict the variation trend of the ground settlement around the transmission tower, and to take repair and prevention measures in advance, so as to effectively reduce the occurrence of transmission accidents. In view of the lack of prediction accuracy of BP neural network in land subsidence prediction, this paper innovatively introduces a bulnius optimization (BSO) algorithm, which optimizes the initial value of weight and threshold of BP neural network by adaptive adjustment of inertia weight, so as to build a BSO-BP prediction model of land subsidence. Finally, by comparing the predicted results with the measured data, it is found that the BSO-BP model can predict the ground subsidence around the transmission tower very accurately.