Short-Term Load Forecasting Using Recurrent Neural Networks With Input Attention Mechanism and Hidden Connection Mechanism

Short-Term Load Forecasting Using Recurrent Neural Networks With Input Attention Mechanism and Hidden Connection Mechanism

Short-term load forecasting is a critical task in the smart grid, which can be used to optimize power deployment and reduce power losses. Recurrent neural networks (RNNs) are the most popular deep learning models for short-term load forecasting. However, despite of achieving better forecasting accur...

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Bibliographic Details
Main Authors:	Mingfei Zhang, Zhoutao Yu, Zhenghua Xu
Format:	Article
Language:	English
Published:	IEEE 2020-01-01
Series:	IEEE Access
Subjects:	Short-term load forecasting recurrent neural networks input attention mechanism hidden connection mechanism
Online Access:	https://ieeexplore.ieee.org/document/9214916/

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