This paper proposes a soft sharing multi-task deep learning method for multi-node load forecasting in the power system.
In this regard, this paper proposes a soft sharing multi-task deep learning method for multi-node load forecasting in the power system. It has the following ...
Jun 1, 2022 · Accurate multi-node load forecasting is the key to the safe, reliable, and economical operation of the power system.
Oct 22, 2024 · Multi-energy load forecasting is the prerequisite for energy management and optimal scheduling of integrated energy systems (IES).
A multi-task learning method for multi-energy load forecasting based on synthesis correlation analysis and load participation factor. Applied Energy.
Tan, Multi-node load forecasting based on multi-task learning with modal feature extraction, Eng Appl Artif Intel, № 112 https://doi.org/10.1016/j.engappai ...
The proposed multi-scale feature attention mixture network can achieve accurate short-term load forecasting and is superior to the existing methods.
Missing: modal | Show results with:modal
Dec 12, 2022 · A multi-task learning model is proposed to improve seasonal-to-annual prediction of the Indian Ocean Dipole (IOD).
Multi-node load forecasting based on multi-task learning with modal feature extraction. Mao Tan, Chenglin Hu, Jie Chen, Ling Wang, Zhengmao Li. https://doi ...
Aug 29, 2024 · This paper provides a comprehensive survey on deep-learning-based STELF over the past ten years. It examines the entire forecasting process.