Research on Temporary Occupation Area Determination Technology of Transmission Line Construction Based on Particle Swarm Optimization BP Neural Network Algorithm

With the mechanization of construction technology, such as new technology, the traditional temporary area prediction method can not meet the demand, compared with the conventional construction of mechanized construction of different topography, voltage level, base tower type data more complex, data distribution, a small number of data deviation is more prominent. In this paper, PSO-BP neural network algorithm is introduced to predict the deviation of the temporary area is within ± 5% compared with the actual area, and the average prediction accuracy is 3.91%. Compared with it, the prediction accuracy of the conventional BP neural network algorithm is improved by 41.03%, which provides a measurement basis for the estimation of the temporary area in the construction in the feasibility study and initial stage.