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Improved Deep Learning Model for Forecasting Short-Term Load Based on Random Forest Algorithm and Rough Set Theory
Smart Grid | 更新时间：2025-06-06

    • 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.”
    • Power Generation Technology   Vol. 44, Issue 6, Pages: 889-895(2023)

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

      CLC： TK 01

    • Received：09 March 2023，

      Published：31 December 2023

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  • FENG Yu,SONG Youbin,JIN Sheng,et al.Improved Deep Learning Model for Forecasting Short-Term Load Based on Random Forest Algorithm and Rough Set Theory[J].Power Generation Technology,2023,44(06):889-895. DOI： 10.12096/j.2096-4528.pgt.23013.

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