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

“…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. Finally, the Beluga Whale Optimization (BWO)-tuned STL-PCA-BWO-BiLSTM hybrid model delivered optimal performance on test sets (RMSE = 0.22, MAE = 0.16, MAPE = 0.99%, ), exhibiting 40.7% higher accuracy than unoptimized BiLSTM (MAE = 0.27). …”

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

“…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. Finally, the Beluga Whale Optimization (BWO)-tuned STL-PCA-BWO-BiLSTM hybrid model delivered optimal performance on test sets (RMSE = 0.22, MAE = 0.16, MAPE = 0.99%, ), exhibiting 40.7% higher accuracy than unoptimized BiLSTM (MAE = 0.27). …”

Figure of ablation experiment. by Xiangjuan Liu (618000)

“…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. Finally, the Beluga Whale Optimization (BWO)-tuned STL-PCA-BWO-BiLSTM hybrid model delivered optimal performance on test sets (RMSE = 0.22, MAE = 0.16, MAPE = 0.99%, ), exhibiting 40.7% higher accuracy than unoptimized BiLSTM (MAE = 0.27). …”

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

“…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. Finally, the Beluga Whale Optimization (BWO)-tuned STL-PCA-BWO-BiLSTM hybrid model delivered optimal performance on test sets (RMSE = 0.22, MAE = 0.16, MAPE = 0.99%, ), exhibiting 40.7% higher accuracy than unoptimized BiLSTM (MAE = 0.27). …”

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

“…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. Finally, the Beluga Whale Optimization (BWO)-tuned STL-PCA-BWO-BiLSTM hybrid model delivered optimal performance on test sets (RMSE = 0.22, MAE = 0.16, MAPE = 0.99%, ), exhibiting 40.7% higher accuracy than unoptimized BiLSTM (MAE = 0.27). …”

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

“…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. Finally, the Beluga Whale Optimization (BWO)-tuned STL-PCA-BWO-BiLSTM hybrid model delivered optimal performance on test sets (RMSE = 0.22, MAE = 0.16, MAPE = 0.99%, ), exhibiting 40.7% higher accuracy than unoptimized BiLSTM (MAE = 0.27). …”

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

“…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. Finally, the Beluga Whale Optimization (BWO)-tuned STL-PCA-BWO-BiLSTM hybrid model delivered optimal performance on test sets (RMSE = 0.22, MAE = 0.16, MAPE = 0.99%, ), exhibiting 40.7% higher accuracy than unoptimized BiLSTM (MAE = 0.27). …”

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

“…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. Finally, the Beluga Whale Optimization (BWO)-tuned STL-PCA-BWO-BiLSTM hybrid model delivered optimal performance on test sets (RMSE = 0.22, MAE = 0.16, MAPE = 0.99%, ), exhibiting 40.7% higher accuracy than unoptimized BiLSTM (MAE = 0.27). …”

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

“…Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. Finally, the Beluga Whale Optimization (BWO)-tuned STL-PCA-BWO-BiLSTM hybrid model delivered optimal performance on test sets (RMSE = 0.22, MAE = 0.16, MAPE = 0.99%, ), exhibiting 40.7% higher accuracy than unoptimized BiLSTM (MAE = 0.27). …”

Test equipment. by Haotian Guo (6620120)

“…The cryostructure exhibited a reticulated pattern, and its width increased from 3–4 cm to 6–7 cm with increasing cooling rate under the same water supply condition. The cooling rate significantly affected the frost heave ratio: under closed conditions, the ratio decreased, whereas under open water supply conditions, the vertical frost heave displacement increased with higher cooling rates.Moisture migration within the specimen was notably different under the two replenishment conditions. …”

Test Schedule. by Haotian Guo (6620120)

“…The cryostructure exhibited a reticulated pattern, and its width increased from 3–4 cm to 6–7 cm with increasing cooling rate under the same water supply condition. The cooling rate significantly affected the frost heave ratio: under closed conditions, the ratio decreased, whereas under open water supply conditions, the vertical frost heave displacement increased with higher cooling rates.Moisture migration within the specimen was notably different under the two replenishment conditions. …”

Mean amplitude values during a complete 360° rotation for the iliocostalis muscle. by Christoph Anders (4068499)

“…The values for the movement half-phase with decreasing load are mirrored to enable a direct comparison between both movement half-phases. …”

Mean amplitude values during a complete 360° rotation for the longissimus muscle. by Christoph Anders (4068499)

“…The values for the movement half-phase with decreasing load are mirrored to enable a direct comparison between both movement half-phases. …”

Mean amplitude values during a complete 360° rotation for the external oblique muscle. by Christoph Anders (4068499)

“…The values for the movement half-phase with decreasing load are mirrored to enable a direct comparison between both movement half-phases. …”

Mean amplitude values during a complete 360° rotation for the internal oblique muscle. by Christoph Anders (4068499)

“…The values for the movement half-phase with decreasing load are mirrored to enable a direct comparison between both movement half-phases. …”

Mean amplitude values during a complete 360° rotation for the rectus abdominis muscle. by Christoph Anders (4068499)

“…The values for the movement half-phase with decreasing load are mirrored to enable a direct comparison between both movement half-phases. …”

Mean amplitude values during a complete 360° rotation for the multifidus muscle. by Christoph Anders (4068499)

“…The values for the movement half-phase with decreasing load are mirrored to enable a direct comparison between both movement half-phases. …”

Mineral component content. by Chuan Li (158692)

“…After cooling, uniaxial compression tests were performed using an electronic universal testing machine to assess their macroscopic properties. …”

Micro-parameters of the numerical model. by Chuan Li (158692)

“…After cooling, uniaxial compression tests were performed using an electronic universal testing machine to assess their macroscopic properties. …”

Microcracks on the surface of the coal sample. by Chuan Li (158692)

“…After cooling, uniaxial compression tests were performed using an electronic universal testing machine to assess their macroscopic properties. …”