A Machine Learning-Optimized System for Pulsatile, Photo- and Chemotherapeutic Treatment Using Near-Infrared Responsive MoS₂‑Based Microparticles in a Breast Cancer Mode... by Maria Kanelli (5494031)

Detailed information of benchmark functions. by Guangwei Liu (181992)

“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”

Evaluation metrics of the models’ performance. by Guangwei Liu (181992)

“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”

Detailed information of datasets. by Guangwei Liu (181992)

“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”

Friedman test results. by Guangwei Liu (181992)

“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”

Average number of selected features. by Guangwei Liu (181992)

“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”

Wilcoxon rank sum test results. by Guangwei Liu (181992)

“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”

Wilcoxon rank sum test results. by Guangwei Liu (181992)

“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”

Average number of selected features. by Guangwei Liu (181992)

“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”

S1 Data - by Guangwei Liu (181992)

“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”

Hybrid feature selection algorithm of CSCO-ROA. by Afnan M. Alhassan (18349378)

“…After the image has been pre-processed, it is segmented using the Thresholding Level set approach. Next, we propose a hybrid chaotic sand cat optimization technique, together with the Remora Optimization Algorithm (ROA) for feature selection. …”

Convergence curves on the functions C19F2, C19F3, C19F5, C19F6, C19F10, C21F2, C21F3, C21F9, and C21F10. by Mahmood A. Jumaah (22272371)

General parameters setting. by Mahmood A. Jumaah (22272371)

“…This paper introduces an improved variation of the FOX optimization algorithm (FOX), termed Improved FOX (IFOX), incorporating a new adaptive method using a dynamically scaled step-size parameter to balance exploration and exploitation based on the current solution’s fitness value. …”

Convergence curves on the functions C17F5, C17F7, C17F8, C17F9, C17F11, C17F19, C17F20, C17F22, and C17F27. by Mahmood A. Jumaah (22272371)

Raw results. by Mahmood A. Jumaah (22272371)

Scalability of the proposed IFOX on C17F8 with the following metrics: Runtime (seconds), Memory usage (MB), and Relative error across problem dimensions (10, 30, 50, 100) and epoch... by Mahmood A. Jumaah (22272371)

The performance results on benchmark test functions and real-world problems. by Mahmood A. Jumaah (22272371)

3D visualization of the Rastrigin function from the CEC 2019 benchmark test functions. by Mahmood A. Jumaah (22272371)

Convergence curves on the functions CL4, CL11, CL13, CL14, CL18, CL19, C17F1, C17F2, and C17F4. by Mahmood A. Jumaah (22272371)

Scalability of IFOX on C17F8: (a) average memory usage, (b) average runtime, and (c) average relative error across epochs (50–1000) for dimensions 10, 30, 50, and 100. by Mahmood A. Jumaah (22272371)