Description of the behaviour of GWO. حسب Ahmed A. Zaki Diab (12757190)

"…<div><p>Recent research has concentrated on emphasizing the significance of incorporating renewable distributed generations (RDGs), like photovoltaic (PV) and wind turbines (WTs), into the distribution system to address issues related to distributed generation (DG) allocation. …"

The optimized results of the 118-Bus. حسب Ahmed A. Zaki Diab (12757190)

"…<div><p>Recent research has concentrated on emphasizing the significance of incorporating renewable distributed generations (RDGs), like photovoltaic (PV) and wind turbines (WTs), into the distribution system to address issues related to distributed generation (DG) allocation. …"

Single line diagram of RDN. حسب Ahmed A. Zaki Diab (12757190)

"…<div><p>Recent research has concentrated on emphasizing the significance of incorporating renewable distributed generations (RDGs), like photovoltaic (PV) and wind turbines (WTs), into the distribution system to address issues related to distributed generation (DG) allocation. …"

Supporting information. حسب Ahmed A. Zaki Diab (12757190)

"…<div><p>Recent research has concentrated on emphasizing the significance of incorporating renewable distributed generations (RDGs), like photovoltaic (PV) and wind turbines (WTs), into the distribution system to address issues related to distributed generation (DG) allocation. …"

LSF for 118 Bus. حسب Ahmed A. Zaki Diab (12757190)

"…<div><p>Recent research has concentrated on emphasizing the significance of incorporating renewable distributed generations (RDGs), like photovoltaic (PV) and wind turbines (WTs), into the distribution system to address issues related to distributed generation (DG) allocation. …"

Fig 3 - حسب Razieh Bidhendi-Yarandi (7139387)

الموضوعات:

The results of the subgroup and meta-regression analyses, stratified by follow-up duration, age, gender, study design, and study setting. حسب Razieh Bidhendi-Yarandi (7139387)

الموضوعات:

Characteristics of studied included. حسب Razieh Bidhendi-Yarandi (7139387)

الموضوعات:

Flowchart of the search process. حسب Razieh Bidhendi-Yarandi (7139387)

الموضوعات:

Funnel plot for testing asymmetry hypothesis using Freeman-Tukey double arcsine transformation for proportions. حسب Razieh Bidhendi-Yarandi (7139387)

الموضوعات:

Results of random effect meta-analysis using Freeman-Tukey double arcsine transformation for proportions, regardless of the duration of their symptoms. حسب Razieh Bidhendi-Yarandi (7139387)

الموضوعات:

Testing set error. 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. …"

Internal structure of an LSTM cell. 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. …"

Prediction effect of each model after STL. 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 kernel density plot for data of each feature. 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 raw data 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. …"

Flowchart of the STL. 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. …"

SARIMA predicts season components. 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. …"

BWO-BiLSTM model 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. …"

Bi-LSTM architecture diagram. 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. …"