Search alternatives:
significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
alter decrease » larger decrease (Expand Search), water decreases (Expand Search), alter disease (Expand Search)
teer decrease » mean decrease (Expand Search), greater decrease (Expand Search)
significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
alter decrease » larger decrease (Expand Search), water decreases (Expand Search), alter disease (Expand Search)
teer decrease » mean decrease (Expand Search), greater decrease (Expand Search)
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3661
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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3662
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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3663
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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3664
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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3665
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3666
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3667
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3668
The long-term <i>in vitro</i> surrogate bacterial viability of canine and feline FMT products frozen at -80°C for six months.
Published 2025“…<p>All canine FMT products exhibited a significant decrease in overall bacterial viability at the six-month timepoint. …”
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3669
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3670
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3671
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3672
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3673
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3677
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3680