Showing 921 - 940 results of 21,342 for search '(( significant ((broader decrease) OR (greater decrease)) ) OR ( significant decrease decrease ))', query time: 0.53s Refine Results
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    Data. by Dong Feng (5375471)

    Published 2025
    Subjects:
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    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. …”
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    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. …”
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    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. …”
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    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. …”
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    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. …”
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