بدائل البحث:
significant decrease » significant increase (توسيع البحث), significantly increased (توسيع البحث)
teer decrease » mean decrease (توسيع البحث), greater decrease (توسيع البحث)
we decrease » _ decrease (توسيع البحث), a decrease (توسيع البحث), nn decrease (توسيع البحث)
significant decrease » significant increase (توسيع البحث), significantly increased (توسيع البحث)
teer decrease » mean decrease (توسيع البحث), greater decrease (توسيع البحث)
we decrease » _ decrease (توسيع البحث), a decrease (توسيع البحث), nn decrease (توسيع البحث)
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3701
Parameter optimization results of BiLSTM.
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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3702
Descriptive statistical analysis of data.
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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3703
The MAE value of the model under raw data.
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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3704
Three error values under raw data.
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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3705
Panel quantile regression results.
منشور في 2024"…The empirical findings show that greater trade openness is associated with significantly higher CO2 emission, additionally; it demonstrates that the influence is heterogeneous across different CO2 emission quantiles in African countries. …"
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3706
Decomposition of time scries plot.
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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3707
Achieving Improved Ion Swarm Shaping Based on Ion Leakage Control in Ion Mobility Spectrometry
منشور في 2025"…In Ion Mobility Spectrometry (IMS), ion gates are essential for controlling ion flow, significantly impacting detection sensitivity and resolution. …"
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3708
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3709
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3710
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3711
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3712
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3713
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3714
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3715
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3716
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3717
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3718
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3719
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3720
Flow diagram representing bromeliad death by overcrowding within the Bromeliad-death procedure.
منشور في 2025الموضوعات: