Showing 741 - 760 results of 13,227 for search '(( significantly ((greatest decrease) OR (linear decrease)) ) OR ( significant increase decrease ))', query time: 0.42s Refine Results
  1. 741

    Changes in total spillage during the third stage (post epidemic). by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
  2. 742

    Dynamics of pairwise net spillovers between sectors in the second stage (in- epidemic). by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
  3. 743

    Sample stage division. by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
  4. 744

    First. by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
  5. 745

    Static spillovers in the first stage (pre-epidemic). by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
  6. 746

    Changes in total spillage during the second stage (in-epidemic). by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
  7. 747

    Dynamics of net spillage in the second stage (in-epidemic). by Cuicui Liu (1496260)

    Published 2024
    Subjects: “…phenomenon intensified significantly…”
  8. 748
  9. 749

    Detailed information of the observation datasets. by Weidong Ji (129916)

    Published 2025
    “…On longer time scales (6–24 hours), the score and correlation between ERA5 and observations further increased, while the centered root-mean-square error (CRMSE) and standard deviation decrease. 4) Hourly wind data with a regular spatial distribution in ERA5 reanalysis provides valuable information for further detailed research on meteorology or renewable energy perspectives, but some inherent shortcomings should be considered.…”
  10. 750

    General technical specification for GW154/6700. by Weidong Ji (129916)

    Published 2025
    “…On longer time scales (6–24 hours), the score and correlation between ERA5 and observations further increased, while the centered root-mean-square error (CRMSE) and standard deviation decrease. 4) Hourly wind data with a regular spatial distribution in ERA5 reanalysis provides valuable information for further detailed research on meteorology or renewable energy perspectives, but some inherent shortcomings should be considered.…”
  11. 751
  12. 752

    Fig 11 - by Naveed Arshad (19712985)

    Published 2024
    Subjects:
  13. 753
  14. 754
  15. 755
  16. 756
  17. 757
  18. 758
  19. 759

    Fig 9 - by Naveed Arshad (19712985)

    Published 2024
    Subjects:
  20. 760