Research on Power Line Loss Degree Prediction Model Based on Artificial Neural Network

In order to improve the prediction accuracy of power line loss degree, this paper analyzes the structure of the artificial neural network model and proposes the quality checking method of line loss data, which lays the foundation for the model to predict the line loss degree. Secondly, we use the equivalent resistance method to calculate the historical grid line loss rate, normalize the data in the input layer of the neural network, so as to improve the accuracy of line loss prediction, and complete the design of the prediction mode of the degree of power line loss based on artificial neural network. The results show that the accuracy, misjudgement rate and omission rate of the line loss prediction model in this paper are 99.32%, 0.45% and 0.23%, respectively, which are better than the other two line loss prediction models, and have strong application advantages.