Research on Relative Error Prediction of Direct Current Charging Pile Based on Deep Learning Algorithm
In response to the increasing number of charging pile constructions and the tendency of equipment devia-tions,a method for relative error prediction of direct current charging piles based on deep learning algorithms is proposed in this paper.Firstly,the dataset collected from the direct current charging piles is preprocessed.Then,LightGBM,N-Linear and CNN models are constructed for relative error prediction,and MAE and MSE are adopted as evaluation metrics.The results indicate that the LightGBM model performs the best,with a decrease of 57.91%in MAE compared to the N-Linear model and a decrease of 30.16%compared to the CNN model.The MSE is reduced by 82.85%compared to the N-Linear model and approximately 47.32%compared to the CNN model.
deep learningrelative errorLightGBMtime series prediction
万方数据
维普
