Multimodal Feature Extraction and Fusion Deep Neural Networks for Short-Term Load Forecasting

Multimodal Feature Extraction and Fusion Deep Neural Networks for Short-Term Load Forecasting

Precise and reliable forecasting of short-term electricity load is essential to the development of smart grids. Particularly, deep neural networks (DNNs) are widely utilized for the prediction of short-term electricity load due to their automatic feature extraction ability. However, these available...

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Bibliographic Details
Main Authors: Zhengmin Kong, Chenggang Zhang, He Lv, Feng Xiong, Zhuolin Fu
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Short-term load forecasting
empirical mode decomposition
similar day methods
deep neural networks
transitional forecasting scheme
electricity price
Online Access:https://ieeexplore.ieee.org/document/9218993/

Internet

https://ieeexplore.ieee.org/document/9218993/

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