Split structural models for belief. by Abigail A. Lee (19935335)

“…<p>Trust in government and positive general vaccine attitudes predicted greater intent to vaccinate. No other latent variables or covariates significantly affected intent to vaccinate. …”

The ASDR of hypertension-related AA in each age group globally predicted by the BAPC model from 2022 to 2050. by Guanghui Yu (423945)

Model A: Logistic structural model. by Abigail A. Lee (19935335)

“…Greater distance from care predicts greater HPV vaccine hesitancy and decreased intent to vaccinate against HPV. …”

Predictions for the annual age-standardized disability-adjusted life years (ASDR) attributable to hepatitis B virus (HBV) infection in China until 2035 on the basis of the Bayesian... by Xinyue Qi (9637055)

The ASDR of hypertension – related AA in different age groups of man worldwide from 2022 to 2050 predicted by the BAPC model. by Guanghui Yu (423945)

The ASDR of hypertension – related AA in different age groups of women worldwide from 2022 to 2050 predicted by the BAPC model. by Guanghui Yu (423945)

Interaction plots for probability of in-hospital death by management group and spleen severity in patients (n = 8073) with AIS≤ = 2 in head/neck, face, chest, extremity, and extern... by Randeep S. Jawa (20489181)

Data cleaning and preparation algorithm. by Ayana Ablayeva (22103708)

“…<div><p>Background</p><p>Liver cancer is the third-deadliest cancer globally, significantly affecting the Asian population, which accounts for 70% of cases. …”

Hydrogen bond interactions between Akt1/Akt2-IN-1 (red) and the AKT2 protein (blue) as predicted by molecular docking analyses. by Sadia Afrin Runa (22504971)

Non-covalent interactions between Akt1/Akt2-IN-1 (ball stick) and the AKT2 protein as predicted by molecular docking analyses. by Sadia Afrin Runa (22504971)

Prediction of the effect of the 9 nsSNPs on AKT2 proteins’ structure and function by eight computational tools. by Sadia Afrin Runa (22504971)

Testing set error. 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. …”

Internal structure of an LSTM cell. 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 kernel density plot for data of each feature. 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. 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. …”

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. …”

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. …”