Pest Bird Density Forecast of Transmission Lines by Random Forest Regression Model and Line Transect Method

The stable operation of power equipment is of great significance to the rapid development of economy. With the continuous strengthening of ecological civilization construction, the number of birds is growing rapidly, bird damage has become one of the main causes of line trip. In this case, it is of great significance to accurately forecast the pest bird distribution density of transmission lines to improve the efficiency of bird prevention. Therefore, this paper proposes a method for predicting the distribution density of birds on transmission lines based on random forest regression and line transect method. Firstly, the main influencing factors of pest bird distribution density are analyzed. Then, the method of fixed-distance line transects and variable-distance line transects is used to investigate the distribution density of pest birds in typical transmission lines and build the original dataset. Finally, three pest bird distribution density prediction models based on linear regression, decision tree regression and random forest regression are established for comparative experiments. The experimental results show that the random forest regression model has high accuracy and reliability in forecasting pest bird distribution density of transmission lines.