Showing 121 - 140 results of 32,530 for search '(( 50 mean decrease ) OR ( 5 ((((ng decrease) OR (nn decrease))) OR (we decrease)) ))', query time: 0.37s Refine Results
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    S1 File - by Yonghui Zhang (279832)

    Published 2024
    “…The CSPM, driven by the optimized CSPs, is then evaluated against two independent phenological datasets from Exp. 2 and Exp. 4 described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0302098#pone.0302098.t002" target="_blank">Table 2</a>. Root means square error (RMSE) (mean absolute error (MAE), coefficient of determination (R<sup>2</sup>), and Nash Sutcliffe model efficiency (NSE)) are 15.50 (14.63, 0.96, 0.42), 4.76 (3.92, 0.97, 0.95), 4.69 (3.72, 0.98, 0.95), 3.91 (3.40, 0.99, 0.96) and 12.54 (11.67, 0.95, 0.60), 5.07 (4.61, 0.98, 0.93), 4.97 (4.28, 0.97, 0.94), 4.58 (4.02, 0.98, 0.95) for using one, two, three, and four observed phenological stages in the CSPs estimation. …”
  5. 125

    Detailed information on field experiments. by Yonghui Zhang (279832)

    Published 2024
    “…The CSPM, driven by the optimized CSPs, is then evaluated against two independent phenological datasets from Exp. 2 and Exp. 4 described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0302098#pone.0302098.t002" target="_blank">Table 2</a>. Root means square error (RMSE) (mean absolute error (MAE), coefficient of determination (R<sup>2</sup>), and Nash Sutcliffe model efficiency (NSE)) are 15.50 (14.63, 0.96, 0.42), 4.76 (3.92, 0.97, 0.95), 4.69 (3.72, 0.98, 0.95), 3.91 (3.40, 0.99, 0.96) and 12.54 (11.67, 0.95, 0.60), 5.07 (4.61, 0.98, 0.93), 4.97 (4.28, 0.97, 0.94), 4.58 (4.02, 0.98, 0.95) for using one, two, three, and four observed phenological stages in the CSPs estimation. …”
  6. 126

    List of symbols used in this study. by Yonghui Zhang (279832)

    Published 2024
    “…The CSPM, driven by the optimized CSPs, is then evaluated against two independent phenological datasets from Exp. 2 and Exp. 4 described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0302098#pone.0302098.t002" target="_blank">Table 2</a>. Root means square error (RMSE) (mean absolute error (MAE), coefficient of determination (R<sup>2</sup>), and Nash Sutcliffe model efficiency (NSE)) are 15.50 (14.63, 0.96, 0.42), 4.76 (3.92, 0.97, 0.95), 4.69 (3.72, 0.98, 0.95), 3.91 (3.40, 0.99, 0.96) and 12.54 (11.67, 0.95, 0.60), 5.07 (4.61, 0.98, 0.93), 4.97 (4.28, 0.97, 0.94), 4.58 (4.02, 0.98, 0.95) for using one, two, three, and four observed phenological stages in the CSPs estimation. …”
  7. 127

    Data sources for calibration and evaluation. by Yonghui Zhang (279832)

    Published 2024
    “…The CSPM, driven by the optimized CSPs, is then evaluated against two independent phenological datasets from Exp. 2 and Exp. 4 described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0302098#pone.0302098.t002" target="_blank">Table 2</a>. Root means square error (RMSE) (mean absolute error (MAE), coefficient of determination (R<sup>2</sup>), and Nash Sutcliffe model efficiency (NSE)) are 15.50 (14.63, 0.96, 0.42), 4.76 (3.92, 0.97, 0.95), 4.69 (3.72, 0.98, 0.95), 3.91 (3.40, 0.99, 0.96) and 12.54 (11.67, 0.95, 0.60), 5.07 (4.61, 0.98, 0.93), 4.97 (4.28, 0.97, 0.94), 4.58 (4.02, 0.98, 0.95) for using one, two, three, and four observed phenological stages in the CSPs estimation. …”
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    Fig 9 - by Dennis Ochola (11626912)

    Published 2022
    Subjects:
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    Fig 7 - by Dennis Ochola (11626912)

    Published 2022
    Subjects:
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    Fig 4 - by Dennis Ochola (11626912)

    Published 2022
    Subjects:
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