يعرض 581 - 600 نتائج من 21,342 نتيجة بحث عن '(( significant reductions decrease ) OR ( significant decrease decrease ))', وقت الاستعلام: 0.45s تنقيح النتائج
  1. 581
  2. 582

    RipU<sup>K60</sup> decreases microtubule abundance at 48 hours post infiltration. حسب Rachel Hiles (20477573)

    منشور في 2024
    "…(B) Heterologous expression of RipU<sup>K60</sup> significantly decreased microtubule number compared to controls at 48 hpi in <i>N</i>. …"
  3. 583
  4. 584
  5. 585
  6. 586

    Fig 6 - حسب Kirralise J. Hansford (20670869)

    منشور في 2025
    الموضوعات:
  7. 587

    Fig 5 - حسب Kirralise J. Hansford (20670869)

    منشور في 2025
    الموضوعات:
  8. 588

    Fig 4 - حسب Kirralise J. Hansford (20670869)

    منشور في 2025
    الموضوعات:
  9. 589
  10. 590
  11. 591

    Testing set error. حسب Xiangjuan Liu (618000)

    منشور في 2025
    "…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. …"
  12. 592

    Internal structure of an LSTM cell. حسب Xiangjuan Liu (618000)

    منشور في 2025
    "…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. …"
  13. 593

    Prediction effect of each model after STL. حسب Xiangjuan Liu (618000)

    منشور في 2025
    "…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. …"
  14. 594

    The kernel density plot for data of each feature. حسب Xiangjuan Liu (618000)

    منشور في 2025
    "…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. …"
  15. 595

    Analysis of raw data prediction results. حسب Xiangjuan Liu (618000)

    منشور في 2025
    "…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. …"
  16. 596

    Flowchart of the STL. حسب Xiangjuan Liu (618000)

    منشور في 2025
    "…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. …"
  17. 597

    SARIMA predicts season components. حسب Xiangjuan Liu (618000)

    منشور في 2025
    "…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. …"
  18. 598

    BWO-BiLSTM model prediction results. حسب Xiangjuan Liu (618000)

    منشور في 2025
    "…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. …"
  19. 599

    Bi-LSTM architecture diagram. حسب Xiangjuan Liu (618000)

    منشور في 2025
    "…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. …"
  20. 600

    STL Linear Combination Forecast Graph. حسب Xiangjuan Liu (618000)

    منشور في 2025
    "…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. …"