Interpretable power load forecasting model based on CNN GRU and SHAP
Author:
Affiliation:
1. Shanghai Institute of Technology SIT,Shanghai,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10347554/10347588/10347636.pdf?arnumber=10347636
Reference18 articles.
1. Ultra-short-term power load forecasting based on cluster empirical mode decomposition of CNN-LSTM[J];Liu;Power System Technology,2021
2. Techno‐economic optimization of a grid‐connected hybrid energy system considering electric and thermal load prediction
3. Correlation filter‐based visual tracking via adaptive weighted CNN features fusion
4. Short-term load forecasting model based on Attention-LSTM in electricity market[J];Peng;Power System Technology,2019
5. A hybrid CNN-GRU based probabilistic model for load forecasting from individual household to commercial building
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