Short-Term Power Load Forecasting Based on CEEMDAN-LSTM-CNN Network
ClickBlue Text| Follow“Electrical Engineering” Abstract:Short-term power load is highly random and volatile, making it difficult for traditional load forecasting methods to grasp the patterns of short-term load changes. To improve the accuracy of short-term power load forecasting, we propose a method that integrates Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Long Short-Term Memory … Read more