Short-Term Load Forecasting Based on Adabelief Optimized Temporal Convolutional Network and Gated Recurrent Unit Hybrid Neural Network

Short-Term Load Forecasting Based on Adabelief Optimized Temporal Convolutional Network and Gated Recurrent Unit Hybrid Neural Network

To fully mine the relationship between temporal features in load data, improve the accuracy and efficiency of short-term load forecasting and overcome the difficulties caused by load nonlinearity and volatility in accurate load forecasting. In this paper, a hybrid neural network short-term load fore...

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Bibliographic Details
Main Authors: Hanhong Shi, Lei Wang, Rafal Scherer, Marcin Wozniak, Pengchao Zhang, Wei Wei
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Short-term load forecasting
distance correlation coefficient
adabelief
temporal convolution network
gated recurrent unit
attention mechanism
Online Access:https://ieeexplore.ieee.org/document/9417229/

Internet

https://ieeexplore.ieee.org/document/9417229/

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