Abstract
Power load forecasting is very important for power dispatching. Accurate load forecasting is of great significance for saving energy, reducing generating costs, and improving social and economic benefits. In order to accurately predict the power load, based on BP neural network theory, combined with the advantages of Clementine in dealing with big data and preventing overfitting, a neural network prediction model for large data is constructed.
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