يعرض 3,861 - 3,880 نتائج من 21,342 نتيجة بحث عن '(( significantly ((linear decrease) OR (greater decrease)) ) OR ( significant decrease decrease ))', وقت الاستعلام: 0.56s تنقيح النتائج
  1. 3861

    BWO-BiLSTM model prediction results. حسب Xiangjuan Liu (618000)

    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. …"
  2. 3862

    Bi-LSTM architecture diagram. حسب Xiangjuan Liu (618000)

    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. …"
  3. 3863

    LOSS curves for BWO-BiLSTM model training. حسب Xiangjuan Liu (618000)

    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. …"
  4. 3864

    Analysis of STL-PCA prediction results. حسب Xiangjuan Liu (618000)

    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. …"
  5. 3865

    Accumulated contribution rate of PCA. حسب Xiangjuan Liu (618000)

    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. …"
  6. 3866

    Figure of ablation experiment. حسب Xiangjuan Liu (618000)

    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. …"
  7. 3867

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

    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. …"
  8. 3868

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

    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. …"
  9. 3869

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

    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. …"
  10. 3870

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

    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. …"
  11. 3871

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

    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. …"
  12. 3872

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

    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. …"
  13. 3873
  14. 3874
  15. 3875

    S1 Data - حسب Taher Mohammadizad (19786989)

    منشور في 2024
    الموضوعات:
  16. 3876
  17. 3877

    Raw data of Fig 2-Fig 13 in this study. حسب Wen Wen Zheng (17721404)

    منشور في 2025
    الموضوعات:
  18. 3878

    Primers used in ChIP-PCR. حسب Lorenza Cutrone (21144285)

    منشور في 2025
    الموضوعات:
  19. 3879
  20. 3880