Short-Term Power Load Forecasting Method Based on Improved Sparrow Search Algorithm, Variational Mode Decomposition, and Bidirectional Long Short-Term Memory Neural Network

A short-term power load forecasting method is proposed based on an improved Sparrow Search Algorithm (ISSA), Variational Mode Decomposition (VMD), and Bidirectional Long Short Term Memory (BiLSTM) neural network. First, the SSA is optimized by combining Tent chaotic mapping, reverse learning, and dy...

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Vydáno v:	Energies (Basel) Ročník 17; číslo 21; s. 5280
Hlavní autoři:	Wen, Ming, Liu, Bo, Zhong, Hao, Yu, Zongchao, Chen, Changqing, Yang, Xian, Dai, Xueying, Chen, Lisi
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Basel MDPI AG 01.11.2024
Témata:	Accuracy Algorithms Analysis BiLSTM Distribution (Probability theory) Forecasting Fourier transforms improved variational mode decomposition load forecasting Methods Neural networks Optimization sparrow optimization algorithm Time series Wavelet transforms
ISSN:	1996-1073, 1996-1073
On-line přístup:	Získat plný text
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