Short-Term Electricity Load Forecasting Based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Improved Sparrow Search Algorithm–Convolutional Neural Network–Bidirectional Long Short-Term Memory Model

Accurate power load forecasting plays an important role in smart grid analysis. To improve the accuracy of forecasting through the three-level “decomposition–optimization–prediction” innovation, this study proposes a prediction model that integrates complete ensemble empirical mode decomposition wit...

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Autores principales:	Han Qiu, Rong Hu, Jiaqing Chen, Zihao Yuan
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	MDPI AG 2025-02-01
Colección:	Mathematics
Materias:	short-term load forecasting CEEMDAN convolutional neural network bidirectional long short-term memory improved sparrow search algorithm
Acceso en línea:	https://www.mdpi.com/2227-7390/13/5/813
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