The line loss rate can reflect the management level and economic benefits of the enterprise.The supply and sale of electricity in different periods will cause errors in the line loss statistics,so short-term electricity forecasting is needed.To solve the problems that the existing approaches cannot fully mine the factors affecting the electricity,a short-term electricity forecast approach based on feature construction and CAE-LSTMis proposed.Features were constructed by data analysis,and MIC was employed for screening.ARIMA was employed to forecast the electricity value and new data was reconstructed by features.CAE-LSTM was applied to extract the features of the data and get the predicted result.Experimental results show that the proposed approach can extract data features more effectively and achieve higher prediction accuracy.
关键词
数据分析/特征构建/CAE/LSTM/ARIMA/电量预测/最大信息系数
Key words
Data analysis/Feature construction/CAE/LSTM/ARIMA/Electricity forecasting/Maximum infor-mation coefficient
维普
万方数据