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significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
significant 17 » significant _ (Expand Search), significant co (Expand Search), significant gap (Expand Search)
17 decrease » _ decrease (Expand Search), a decrease (Expand Search), nn decrease (Expand Search)
significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
significant 17 » significant _ (Expand Search), significant co (Expand Search), significant gap (Expand Search)
17 decrease » _ decrease (Expand Search), a decrease (Expand Search), nn decrease (Expand Search)
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2701
Figure of ablation experiment.
Published 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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2702
Results from cross sectional dependence test.
Published 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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2703
Flowchart of the STL-PCA-BWO-BiLSTM model.
Published 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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2704
Parameter optimization results of BiLSTM.
Published 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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2705
Descriptive statistical analysis of data.
Published 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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2706
The MAE value of the model under raw data.
Published 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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2707
Three error values under raw data.
Published 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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2708
Panel quantile regression results.
Published 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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2709
Decomposition of time scries plot.
Published 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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2710
Achieving Improved Ion Swarm Shaping Based on Ion Leakage Control in Ion Mobility Spectrometry
Published 2025“…In Ion Mobility Spectrometry (IMS), ion gates are essential for controlling ion flow, significantly impacting detection sensitivity and resolution. …”
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2711
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2712
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2713
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2714
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2715
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2716
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2717
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2718
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2719
Fractal dimension evolution of oil droplet flame under different spray hole diameter.
Published 2025Subjects: -
2720
Evolution of flame fractal dimension of oil droplets with different volumes.
Published 2025Subjects: