Showing 601 - 620 results of 921 for search '"Jilin"', query time: 0.05s Refine Results
  1. 601
  2. 602
  3. 603
  4. 604
  5. 605
  6. 606

    Multivariate Load Forecasting of Integrated Energy System Based on CEEMDAN-CSO-LSTM-MTL by WANG Yongli, LIU Zeqiang, DONG Huanran, LI Dexin, CHEN Xin, GUO Lu, WANG Jiarui

    Published 2025-01-01
    “…Firstly,preprocess the collected raw load data and calculate the actual load value considering system energy loss; Secondly,the maximum information coefficient (MIC) is used to analyze the correlation between multiple loads and between multiple loads and weather factors,and to extract strongly correlated variables of multiple loads; Once again,the strongly correlated variables of multiple loads are substituted into CEEMDAN,and the load data is decomposed into stationary subsequences; Then,the feature sequence is substituted into the LSTM-MTL shared layer and the CSO algorithm is used to optimize the prediction model,achieving collaborative prediction of multiple loads; Finally,the performance of the constructed model was validated using a multivariate load dataset from a chemical park in Jilin City,Jilin Province,China. The results show that compared with traditional prediction models,the constructed model can effectively improve the prediction accuracy of multiple loads in the integrated energy system.…”
    Get full text
    Article
  7. 607
  8. 608
  9. 609
  10. 610
  11. 611
  12. 612
  13. 613
  14. 614
  15. 615
  16. 616
  17. 617
  18. 618
  19. 619
  20. 620