Bi-LSTM architecture diagram. by 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. …”

STL Linear Combination Forecast Graph. by 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. …”

LOSS curves for BWO-BiLSTM model training. by 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. by 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. by 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. by 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. by 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. by 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. by 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. by 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. by 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. by 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 of higher-level hyperemic coronary flow increase. by Eisuke Usui (12111855)

Image_1_Decreased Endometrial Thickness Is Associated With Higher Risk of Neonatal Complications in Women With Polycystic Ovary Syndrome.tif by Jialyu Huang (6742409)

“…Compared to women with EMT >13 mm, women with EMT ≤8 mm also had significantly higher risk of PTB (adjusted OR 3.79, 95% CI 1.53–9.39; P = 0.004), LBW (adjusted OR 4.33, 95% CI 1.39–13.50; P = 0.012) and SGA (adjusted OR 6.38, 95% CI 1.78–22.83; P = 0.004). …”

Image_2_Decreased Endometrial Thickness Is Associated With Higher Risk of Neonatal Complications in Women With Polycystic Ovary Syndrome.tif by Jialyu Huang (6742409)

“…Compared to women with EMT >13 mm, women with EMT ≤8 mm also had significantly higher risk of PTB (adjusted OR 3.79, 95% CI 1.53–9.39; P = 0.004), LBW (adjusted OR 4.33, 95% CI 1.39–13.50; P = 0.012) and SGA (adjusted OR 6.38, 95% CI 1.78–22.83; P = 0.004). …”

Table_1_Decreased Endometrial Thickness Is Associated With Higher Risk of Neonatal Complications in Women With Polycystic Ovary Syndrome.docx by Jialyu Huang (6742409)

“…Compared to women with EMT >13 mm, women with EMT ≤8 mm also had significantly higher risk of PTB (adjusted OR 3.79, 95% CI 1.53–9.39; P = 0.004), LBW (adjusted OR 4.33, 95% CI 1.39–13.50; P = 0.012) and SGA (adjusted OR 6.38, 95% CI 1.78–22.83; P = 0.004). …”

Analysis of the significantly different metabolomic features. by Bhuripit Saraphol (20855573)

Subjects:

Clinical significance of CD44V expression in primary colon cancer tissues. by Takeshi Kaida (6532907)

Subjects:

Repeated measures ANOVA on T1 accuracy. by Leon C. Reteig (5713010)

Descriptive statistics for T2|T1 accuracy. by Leon C. Reteig (5713010)