Showing 2,701 - 2,720 results of 21,342 for search '(( significant 17 decrease ) OR ( significant decrease decrease ))', query time: 0.50s Refine Results
  1. 2701

    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. 2702

    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. 2703

    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. 2704

    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. 2705

    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. 2706

    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. 2707

    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. 2708

    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. 2709

    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. 2710

    Achieving Improved Ion Swarm Shaping Based on Ion Leakage Control in Ion Mobility Spectrometry by Jiyao Wang (2121157)

    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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