بدائل البحث:
linear decrease » linear increase (توسيع البحث)
larger decrease » marked decrease (توسيع البحث)
nn decrease » _ decrease (توسيع البحث), mean decrease (توسيع البحث), gy decreased (توسيع البحث)
a decrease » _ decrease (توسيع البحث), _ decreased (توسيع البحث), _ decreases (توسيع البحث)
linear decrease » linear increase (توسيع البحث)
larger decrease » marked decrease (توسيع البحث)
nn decrease » _ decrease (توسيع البحث), mean decrease (توسيع البحث), gy decreased (توسيع البحث)
a decrease » _ decrease (توسيع البحث), _ decreased (توسيع البحث), _ decreases (توسيع البحث)
-
5061
LOSS curves for BWO-BiLSTM model training.
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. …"
-
5062
Analysis of STL-PCA prediction results.
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. …"
-
5063
Accumulated contribution rate of PCA.
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. …"
-
5064
Figure of ablation experiment.
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. …"
-
5065
Flowchart of the STL-PCA-BWO-BiLSTM model.
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. …"
-
5066
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. …"
-
5067
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. …"
-
5068
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. …"
-
5069
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. …"
-
5070
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. …"
-
5071
Risk of bias summary.
منشور في 2025"…The observed decrease in body weight could be partially attributed to factors influencing energy balance, as evidenced by the significantly lower mean calorie intake at the end of the intervention (1694.71 kcal/day, 95% CI: 1498.57–1890.85) compared to the baseline intake (2000.64 kcal/day, 95% CI: 1830–2172.98), despite the absence of intentional efforts to restrict energy intake by the participants. …"
-
5072
Criteria for study selection.
منشور في 2025"…The observed decrease in body weight could be partially attributed to factors influencing energy balance, as evidenced by the significantly lower mean calorie intake at the end of the intervention (1694.71 kcal/day, 95% CI: 1498.57–1890.85) compared to the baseline intake (2000.64 kcal/day, 95% CI: 1830–2172.98), despite the absence of intentional efforts to restrict energy intake by the participants. …"
-
5073
Estimated results of the mediation effect.
منشور في 2024"…Besides the result from the double threshold model reveals a complex, nonlinear relationship between trade openness and CO2 emissions in Africa. …"
-
5074
Panel unit root test result.
منشور في 2024"…Besides the result from the double threshold model reveals a complex, nonlinear relationship between trade openness and CO2 emissions in Africa. …"
-
5075
Kernel density estimation for CO2.
منشور في 2024"…Besides the result from the double threshold model reveals a complex, nonlinear relationship between trade openness and CO2 emissions in Africa. …"
-
5076
Change in panel quantile regression coefficients.
منشور في 2024"…Besides the result from the double threshold model reveals a complex, nonlinear relationship between trade openness and CO2 emissions in Africa. …"
-
5077
Definitions of variables and measurements.
منشور في 2024"…Besides the result from the double threshold model reveals a complex, nonlinear relationship between trade openness and CO2 emissions in Africa. …"
-
5078
Regression estimates: Double threshold model.
منشور في 2024"…Besides the result from the double threshold model reveals a complex, nonlinear relationship between trade openness and CO2 emissions in Africa. …"
-
5079
Results from cross sectional dependence test.
منشور في 2024"…Besides the result from the double threshold model reveals a complex, nonlinear relationship between trade openness and CO2 emissions in Africa. …"
-
5080
Panel quantile regression results.
منشور في 2024"…Besides the result from the double threshold model reveals a complex, nonlinear relationship between trade openness and CO2 emissions in Africa. …"