Showing 961 - 980 results of 34,143 for search '(( significant decrease decrease ) OR ( significantly ((improve decrease) OR (improve disease)) ))*', query time: 0.59s Refine Results
  1. 961

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

    Published 2025
    “…<div><p>This study constructs a multi-stage hybrid forecasting model using hog price time series data and its influencing factors to improve prediction accuracy. 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. …”
  2. 962

    Figure of ablation experiment. by Xiangjuan Liu (618000)

    Published 2025
    “…<div><p>This study constructs a multi-stage hybrid forecasting model using hog price time series data and its influencing factors to improve prediction accuracy. 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. …”
  3. 963

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

    Published 2025
    “…<div><p>This study constructs a multi-stage hybrid forecasting model using hog price time series data and its influencing factors to improve prediction accuracy. 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. …”
  4. 964

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

    Published 2025
    “…<div><p>This study constructs a multi-stage hybrid forecasting model using hog price time series data and its influencing factors to improve prediction accuracy. 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. …”
  5. 965

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

    Published 2025
    “…<div><p>This study constructs a multi-stage hybrid forecasting model using hog price time series data and its influencing factors to improve prediction accuracy. 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. …”
  6. 966

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

    Published 2025
    “…<div><p>This study constructs a multi-stage hybrid forecasting model using hog price time series data and its influencing factors to improve prediction accuracy. 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. …”
  7. 967

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

    Published 2025
    “…<div><p>This study constructs a multi-stage hybrid forecasting model using hog price time series data and its influencing factors to improve prediction accuracy. 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. …”
  8. 968

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

    Published 2025
    “…<div><p>This study constructs a multi-stage hybrid forecasting model using hog price time series data and its influencing factors to improve prediction accuracy. 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. …”
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