Design of power demand forecasting and marketing service platform based on deep learning

In this paper, RNN (Recurrent neural network) model in DL (Deep Learning) is adopted, and a large-scale RNN model is constructed by using historical power load data and other related information. The model is used to forecast the future power load, and applied to the power demand forecasting and marketing service platform. In addition, the selection and optimization methods of model parameters and superparameters are analyzed, which further improves the prediction effect of the model. Through the training and optimization of the model, the prediction accuracy and practicability are improved, and the marketing service efficiency and enterprise income are also improved. Through the experimental verification, this model can get a recall rate of 95.62%, which is better than the traditional CNN model. In addition, after many iterations, the accuracy of this model in power demand forecasting has obvious advantages over the traditional CNN model.