Showing 3,201 - 3,220 results of 21,342 for search '(( significant decrease decrease ) OR ( significant broader decrease ))', query time: 0.64s Refine Results
  1. 3201
  2. 3202
  3. 3203
  4. 3204
  5. 3205
  6. 3206
  7. 3207
  8. 3208
  9. 3209
  10. 3210
  11. 3211
  12. 3212
  13. 3213
  14. 3214
  15. 3215

    Major hyperparameters of RF-SVR. by Jintao Li (448681)

    Published 2024
    “…Similarly, at the Lianghekou station, for a one-month lead prediction period, the RF-MLPR model’s R<sup>2</sup> value was 7.9% higher than that of the RF-SVR model. The significance of this research lies not only in its contribution to improving hydrological prediction accuracy but also in its broader applicability. …”
  16. 3216

    Pseudo code for coupling model execution process. by Jintao Li (448681)

    Published 2024
    “…Similarly, at the Lianghekou station, for a one-month lead prediction period, the RF-MLPR model’s R<sup>2</sup> value was 7.9% higher than that of the RF-SVR model. The significance of this research lies not only in its contribution to improving hydrological prediction accuracy but also in its broader applicability. …”
  17. 3217

    Major hyperparameters of RF-MLPR. by Jintao Li (448681)

    Published 2024
    “…Similarly, at the Lianghekou station, for a one-month lead prediction period, the RF-MLPR model’s R<sup>2</sup> value was 7.9% higher than that of the RF-SVR model. The significance of this research lies not only in its contribution to improving hydrological prediction accuracy but also in its broader applicability. …”
  18. 3218

    Results of RF algorithm screening factors. by Jintao Li (448681)

    Published 2024
    “…Similarly, at the Lianghekou station, for a one-month lead prediction period, the RF-MLPR model’s R<sup>2</sup> value was 7.9% higher than that of the RF-SVR model. The significance of this research lies not only in its contribution to improving hydrological prediction accuracy but also in its broader applicability. …”
  19. 3219

    Schematic diagram of the basic principles of SVR. by Jintao Li (448681)

    Published 2024
    “…Similarly, at the Lianghekou station, for a one-month lead prediction period, the RF-MLPR model’s R<sup>2</sup> value was 7.9% higher than that of the RF-SVR model. The significance of this research lies not only in its contribution to improving hydrological prediction accuracy but also in its broader applicability. …”
  20. 3220