بدائل البحث:
significant decrease » significant increase (توسيع البحث), significantly increased (توسيع البحث)
linear decrease » linear increase (توسيع البحث)
a decrease » _ decrease (توسيع البحث), _ decreased (توسيع البحث), _ decreases (توسيع البحث)
significant decrease » significant increase (توسيع البحث), significantly increased (توسيع البحث)
linear decrease » linear increase (توسيع البحث)
a decrease » _ decrease (توسيع البحث), _ decreased (توسيع البحث), _ decreases (توسيع البحث)
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3461
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3462
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3463
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3464
GWAS analysis identifies several single nucleotide polymorphisms (SNPs) that are associated with the changes in viral copies.
منشور في 2024"…<p>(A) Genome-wide association results of the impact of identified SNPs on viral copies during SARS-CoV-2 infection. …"
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3465
GWAS analysis identifies several single nucleotide polymorphisms (SNPs) that are associated with the changes in viral copies.
منشور في 2024"…<p>(A) Genome-wide association results of the impact of identified SNPs on viral copies during SARS-CoV-2 infection. …"
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3466
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3467
GWAS analysis using Cluster 2 data (shown in S1 Fig).
منشور في 2024"…<p>(A) Genome-wide association results of the impact of identified SNPs on viral copies during SARS-CoV-2 infection. …"
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3468
GWAS analysis using only Cluster 1 data (shown in S1 Fig).
منشور في 2024"…<p>(A) Genome-wide association results of the impact of identified SNPs on viral copies during SARS-CoV-2 infection. …"
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3469
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3470
GWAS analysis using Cluster 3 data (shown in S1 Fig).
منشور في 2024"…<p>(A) Genome-wide association results of the impact of identified SNPs on viral copies during SARS-CoV-2 infection. …"
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3471
GWAS analysis using Cluster 4 data (shown in S1 Fig).
منشور في 2024"…<p>(A) Genome-wide association results of the impact of identified SNPs on viral copies during SARS-CoV-2 infection. …"
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3472
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3473
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3474
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3475
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3476
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3477
Testing set error.
منشور في 2025"…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. …"
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3478
Internal structure of an LSTM cell.
منشور في 2025"…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. …"
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3479
Prediction effect of each model after STL.
منشور في 2025"…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. …"
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3480
The kernel density plot for data of each feature.
منشور في 2025"…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. …"