Feature selection convergence time comparison of various binary metaheuristic algorithms. حسب Amal H. Alharbi (21755906)

Histograms of various water quality parameters, including pH, Hardness, Solids, Chloramines, Sulfate, Organic Carbon, Trihalomethanes, Turbidity, and a binary portability check. حسب Amal H. Alharbi (21755906)

Confusion matrix for a binary outcome (adapted from Fawcett [30]). حسب João Albuquerque (12936572)

Statistical summary of all models. حسب Amal H. Alharbi (21755906)

"…This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …"

Classification performance of ML and DL models. حسب Amal H. Alharbi (21755906)

"…This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …"

Hyperparameters of the LSTM Model. حسب Ahmed M. Elshewey (21463867)

"…Out of all the models, LSTM produced the best results. The AD-PSO-Guided WOA algorithm was used to adjust the hyperparameters for the LSTM model. …"

Prediction results of individual models. حسب Ahmed M. Elshewey (21463867)

"…Out of all the models, LSTM produced the best results. The AD-PSO-Guided WOA algorithm was used to adjust the hyperparameters for the LSTM model. …"

Classification performance after optimization. حسب Amal H. Alharbi (21755906)

"…This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …"

ANOVA test for optimization results. حسب Amal H. Alharbi (21755906)

"…This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …"

Wilcoxon test results for optimization. حسب Amal H. Alharbi (21755906)

"…This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …"

Wilcoxon test results for feature selection. حسب Amal H. Alharbi (21755906)

"…This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …"

Feature selection metrics and their definitions. حسب Amal H. Alharbi (21755906)

"…This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …"

Feature selection results. حسب Amal H. Alharbi (21755906)

"…This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …"

ANOVA test for feature selection. حسب Amal H. Alharbi (21755906)

"…This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …"

The AD-PSO-Guided WOA LSTM framework. حسب Ahmed M. Elshewey (21463867)

"…Out of all the models, LSTM produced the best results. The AD-PSO-Guided WOA algorithm was used to adjust the hyperparameters for the LSTM model. …"

Classification baseline performance. حسب Doaa Sami Khafaga (21463870)

"…These findings highlight the potential of metaheuristic optimization techniques to improve the effectiveness of deep learning models in clinical diagnostics quantifiably. …"

Feature selection results. حسب Doaa Sami Khafaga (21463870)

"…These findings highlight the potential of metaheuristic optimization techniques to improve the effectiveness of deep learning models in clinical diagnostics quantifiably. …"

ANOVA test result. حسب Doaa Sami Khafaga (21463870)

"…These findings highlight the potential of metaheuristic optimization techniques to improve the effectiveness of deep learning models in clinical diagnostics quantifiably. …"

Summary of literature review. حسب Doaa Sami Khafaga (21463870)

"…These findings highlight the potential of metaheuristic optimization techniques to improve the effectiveness of deep learning models in clinical diagnostics quantifiably. …"

Fitting single-molecule data with the full stochastic model. حسب Luis U. Aguilera (3759934)