Search alternatives:
significantly reduce » significantly reduced (Expand Search), significantly greater (Expand Search), significantly enhance (Expand Search)
significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
reduce decrease » reduce disease (Expand Search), reduce depressive (Expand Search), induces decreased (Expand Search)
significantly reduce » significantly reduced (Expand Search), significantly greater (Expand Search), significantly enhance (Expand Search)
significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
reduce decrease » reduce disease (Expand Search), reduce depressive (Expand Search), induces decreased (Expand Search)
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1941
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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1942
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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1943
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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1944
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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1945
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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1946
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1947
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1948
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1949
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1950
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1951
Between-group differences in 95% Area, Y Sway Amplitude and LFS during postural training.
Published 2025Subjects: -
1952
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1953
Consolidation of training-induced changes in unipedal stance: 95% Area, Y Sway Amplitude and LFS.
Published 2025Subjects: -
1954
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1955
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1956
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1957
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1958
Vertebral cancellous tissueμCT parameters are not significantly affected by aging from 16 to 21 weeks, housing type, or microgravity.
Published 2025“…Nonsignificant trends implicate an effect of spaceflight reducing BV/TV, increasing DA, and reducing Tb.N. Data shown are the mean ± standard deviation with a scatter plot (ns: non-significant). …”
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1959
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1960