يعرض 1,101 - 1,120 نتائج من 21,342 نتيجة بحث عن '(( significant decrease decrease ) OR ( significance ((test decrease) OR (greatest decrease)) ))', وقت الاستعلام: 0.58s تنقيح النتائج
  1. 1101
  2. 1102
  3. 1103
  4. 1104

    WDR12 associates with Aurora B. حسب Zachary J. Hough (20840430)

    منشور في 2025
    الموضوعات:
  5. 1105
  6. 1106
  7. 1107
  8. 1108
  9. 1109
  10. 1110
  11. 1111
  12. 1112
  13. 1113

    Base-case analysis. حسب Yiping An (20609789)

    منشور في 2025
    الموضوعات:
  14. 1114

    Cost-effectiveness acceptability curve. حسب Yiping An (20609789)

    منشور في 2025
    الموضوعات:
  15. 1115

    Markov model. حسب Yiping An (20609789)

    منشور في 2025
    الموضوعات:
  16. 1116
  17. 1117

    One-way sensitivity analysis. حسب Yiping An (20609789)

    منشور في 2025
    الموضوعات:
  18. 1118

    ICER changes with time horizon. حسب Yiping An (20609789)

    منشور في 2025
    الموضوعات:
  19. 1119

    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. Finally, the Beluga Whale Optimization (BWO)-tuned STL-PCA-BWO-BiLSTM hybrid model delivered optimal performance on test sets (RMSE = 0.22, MAE = 0.16, MAPE = 0.99%, ), exhibiting 40.7% higher accuracy than unoptimized BiLSTM (MAE = 0.27). …"
  20. 1120

    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. Finally, the Beluga Whale Optimization (BWO)-tuned STL-PCA-BWO-BiLSTM hybrid model delivered optimal performance on test sets (RMSE = 0.22, MAE = 0.16, MAPE = 0.99%, ), exhibiting 40.7% higher accuracy than unoptimized BiLSTM (MAE = 0.27). …"