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This paper proposes a load forecasting method based on LSTM model, fully explores the regularity of historical load data of industrial park enterprises, inputs the data features into LSTM units for feature extraction, and applies the attention-based model for load forecasting. The experiments show that the accuracy of our prediction model and early warning model is better than that of the baseline and can reach the standard of application in practice; this model can also be used for earlydoi:10.1155/2021/1435334 fatcat:ntlnvgpaxbgfxoukztqxuyjmmm