Showing 4,381 - 4,400 results of 21,342 for search '(( significantly ((larger decrease) OR (mean decrease)) ) OR ( significant decrease decrease ))', query time: 0.52s Refine Results
  1. 4381

    Figure of ablation experiment. by Xiangjuan Liu (618000)

    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. …”
  2. 4382

    Results from cross sectional dependence test. by Getachew Magnar Kitila (19935139)

    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. …”
  3. 4383

    Flowchart of the STL-PCA-BWO-BiLSTM model. by Xiangjuan Liu (618000)

    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. …”
  4. 4384

    Parameter optimization results of BiLSTM. by Xiangjuan Liu (618000)

    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. …”
  5. 4385

    Descriptive statistical analysis of data. by Xiangjuan Liu (618000)

    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. …”
  6. 4386

    The MAE value of the model under raw data. by Xiangjuan Liu (618000)

    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. …”
  7. 4387

    Three error values under raw data. by Xiangjuan Liu (618000)

    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. …”
  8. 4388

    Panel quantile regression results. by Getachew Magnar Kitila (19935139)

    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. …”
  9. 4389

    Decomposition of time scries plot. by Xiangjuan Liu (618000)

    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. …”
  10. 4390
  11. 4391

    Characteristics of children in the study. by Shijie Yu (511369)

    Published 2025
    “…</p><p>Conclusions:</p><p>This study found a significant association between myopia and worse HRQOL in primary and secondary school children. …”
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