بدائل البحث:
significant reductions » significant reduction (توسيع البحث), significant predictors (توسيع البحث), significant variations (توسيع البحث)
significant decrease » significant increase (توسيع البحث), significantly increased (توسيع البحث)
reductions decrease » reduction decreased (توسيع البحث)
significant reductions » significant reduction (توسيع البحث), significant predictors (توسيع البحث), significant variations (توسيع البحث)
significant decrease » significant increase (توسيع البحث), significantly increased (توسيع البحث)
reductions decrease » reduction decreased (توسيع البحث)
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581
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582
RipU<sup>K60</sup> decreases microtubule abundance at 48 hours post infiltration.
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>. …"
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583
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584
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585
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586
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587
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588
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589
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590
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591
Testing set error.
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. …"
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592
Internal structure of an LSTM cell.
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. …"
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593
Prediction effect of each model after STL.
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. …"
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594
The kernel density plot for data of each feature.
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. …"
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595
Analysis of raw data prediction results.
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. …"
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596
Flowchart of the STL.
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. …"
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597
SARIMA predicts season components.
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. …"
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598
BWO-BiLSTM model prediction results.
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. …"
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599
Bi-LSTM architecture diagram.
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. …"
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600
STL Linear Combination Forecast Graph.
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. …"