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

An improved Grey Wolf Optimization based heuristic initialization algorithm for feature selection in P2P lending default prediction by Muhammad Sam'an (20649621)

The flowchart showing the optimization process of the hybrid methods using BEOSA as the base algorithm and SA and FFA as integrated algorithms. by Olaide N. Oyelade (14047002)

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The result of the accuracy of tested algorithms. by Nebojsa Bacanin (13932723)

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Feature selection ratio results for tested algorithms. by Nebojsa Bacanin (13932723)

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Best fitness value results for tested algorithms. by Nebojsa Bacanin (13932723)

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Mean fitness value results for tested algorithms. by Nebojsa Bacanin (13932723)

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Standard deviation of fitness value results for tested algorithms. by Nebojsa Bacanin (13932723)

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Optimizing Kernel Transformations to Handle Binary Class Imbalanced Dataset Classification by Vaibhavi Patel (19843282)

a) Accuracy and b) selected feature size of algorithms on the COVID-19 dataset. by Nebojsa Bacanin (13932723)

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Image 1_A novel inversion method of slope rock mechanical parameters using differential evolution gray wolf algorithm to optimize support vector regression.tif by Tingkai Hou (21014762)

“…</p>Methods<p>This paper proposes a displacement back-analysis (DBA) approach that utilizes support vector regression (SVR) optimized by differential evolution grey wolf algorithm (DE-GWO) to invert the RMMPs, which improves global optimization capability and inversion accuracy. …”

Image 2_A novel inversion method of slope rock mechanical parameters using differential evolution gray wolf algorithm to optimize support vector regression.tif by Tingkai Hou (21014762)

“…</p>Methods<p>This paper proposes a displacement back-analysis (DBA) approach that utilizes support vector regression (SVR) optimized by differential evolution grey wolf algorithm (DE-GWO) to invert the RMMPs, which improves global optimization capability and inversion accuracy. …”

Boxplots analysis of the tested algorithms using average error rate across 21 datasets. by Nebojsa Bacanin (13932723)

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Schematic of iteration process of IDE-IIGA. by Ling Zhao (111365)

An optimization process of the proposed hybrid BEOSA (HBEOSA) combining both SA and FFA methods into BEOSA. by Olaide N. Oyelade (14047002)

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Feature selection process. by Balraj Preet Kaur (20370832)

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

Proposed Algorithm. by Hend Bayoumi (22693738)

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Homomorphic binary tree. by Jianhua He (341366)

<i>hi</i>PRS algorithm process flow. by Michela C. Massi (14599915)