Showing 3,841 - 3,860 results of 21,342 for search '(( significantly affected decrease ) OR ( significant decrease decrease ))', query time: 0.61s Refine Results
  1. 3841

    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. …”
  2. 3842

    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. …”
  3. 3843

    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. …”
  4. 3844

    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. …”
  5. 3845

    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. …”
  6. 3846

    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. …”
  7. 3847

    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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  11. 3851

    Demographic characteristics of participants. by Evelyn Aboagye Addae (22648064)

    Published 2025
    “…Again, change in positive affect and change in subjective feeling of unsafety significantly mediated the effect of fear of COVID-19 on composite SWB and only change in positive affect mediated the effect of fear of COVID-19 on subjective happiness. …”
  12. 3852

    Participant characteristics and study measures. by Evelyn Aboagye Addae (22648064)

    Published 2025
    “…Again, change in positive affect and change in subjective feeling of unsafety significantly mediated the effect of fear of COVID-19 on composite SWB and only change in positive affect mediated the effect of fear of COVID-19 on subjective happiness. …”
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