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

"…<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. …"

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

"…<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. …"

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

"…<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. …"

Figure of ablation experiment. حسب Xiangjuan Liu (618000)

"…<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. …"

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

"…<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. …"

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

"…<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. …"

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

"…<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. …"

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

"…<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. …"

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

"…<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. …"

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

"…<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. …"

Autophagy significantly increases RGCs loss. حسب Hongmei Qian (538647)

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Autophagy significantly increases RGCs loss. حسب Hongmei Qian (538647)

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Variation of the most appropriate p value significance threshold with different ratios of the standard deviations and sample sizes. حسب Farrokh Habibzadeh (12256529)

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Impact on different areas of health. حسب Margherita Molaro (17803989)

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Summary of significance levels for comparison of surgical segment ROM between different test groups. حسب Jia Zhu (135506)

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Study flow chart. حسب Raymond Atwine (18574812)

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Bar graph showing proportion of NADCs. حسب Raymond Atwine (18574812)

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Line graph showing the trends of ADCs and NADCS over the 10 years period. حسب Raymond Atwine (18574812)

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Outcome comparisons of study participant characteristics. حسب Raymond Atwine (18574812)

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Baseline characteristics of study participants. حسب Raymond Atwine (18574812)

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