Hazard Prediction of Transmission Slope Based on GA-SA-SVR Model
Hazard evaluation of transmission slopes is of great significance for the safe operation of transmission lines in China.Relying on the data of transmission line slope hazard investigation and condition assessment of a transmission company,the database was screened,and the six items of distance from the edge of the tower,height of the slope,slope,surrounding land,geotechnical properties,and vegetation were used as the input eigenvalues,and the hazard coefficients were used as the output labels to establish a prediction model using Support Vector Regression(SVR).The Genetic Algorithm(GA)and Simulated Annealing(SA)of the individual optimization algorithm and the combination of optimization algorithms are used to optimize the SVR model,respectively,and set up OOA,HPO and other optimization algorithms as a control group.The results show that the optimization effect of the combination algorithm is better than that of the single algorithm optimization,and the optimization effect of the genetic-simulated annealing combination algorithm(GA-SA)is more advantageous in terms of accuracy and degree of fit,with an R2 of0.937 5 for the test set,an MSE value of 0.001 2,and a fitness function f(x)value of 0.072 4.The model has better prediction performance and is more objective and intelligent compared to the original method.
万方数据
维普
