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Improved Deep Learning Model for Forecasting Short-Term Load Based on Random Forest Algorithm and Rough Set Theory
Power Generation Technology   Vol. 44, Issue 6, Pages: 889-895(2023)
Smart Grid|Updated：2025-06-06
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    • Improved Deep Learning Model for Forecasting Short-Term Load Based on Random Forest Algorithm and Rough Set Theory

    • “In the field of power load forecasting, experts have proposed the RF-DL-RST model, which extracts key feature quantities through the random forest algorithm, trains and corrects prediction results using deep neural networks, and improves prediction accuracy.”

    • DOI：10.12096/j.2096-4528.pgt.23013    

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Related Author

SONG Liye
MENG Fanyu
CHEN Yulin
SONG Xinping

Related Institution

Faculty of Electrical and Control Engineering, Liaoning Technical University
Hainan Institute of Zhejiang University