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

Homomorphic binary tree. by Jianhua He (341366)

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)

Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results by Se-Hee Jo (20554623)

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

Feature selection process. by Balraj Preet Kaur (20370832)

“…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”

RMSE on the test data when fitting (logistic) quadratic models to binary data across increasing measurement error values . by Jakub Stoklosa (3315042)

Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm by Hussein Ali Bardan (21976208)

“…This strategy </p><p dir="ltr">not only improves detection efficiency and accuracy but also supports early diagnosis and treatment planning, </p><p dir="ltr">leading to better patient outcomes. By leveraging the binary GWO algorithm to optimize the feature selection </p><p dir="ltr">process and CNNs for image classification, the proposed approach reduces computational costs while increasing </p><p dir="ltr">classification accuracy. …”

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

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The illustration depicts our CQ-CNN architecture for binary image classification. by Mominul Islam (3513758)

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

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

“…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …”

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

“…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …”

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

“…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …”

Application of ABC SMC to the fitting of the binary flip with cusp model. by Elena Camacho-Aguilar (10906327)

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

“…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …”

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

“…The proposed approach integrates binary feature selection and metaheuristic optimization into a unified optimization process, effectively balancing exploration and exploitation to handle complex, high-dimensional datasets. …”

The workflow diagram for the gene expression biomarker study which involve using principal component analysis (PCA) to reduce the number of features (principal components), thus re... by Aninda Astuti (21736334)

MSE for ILSTM algorithm in binary classification. by Asmaa Ahmed Awad (16726315)

“…Deep learning models (e.g., Long Short-Term Memory, LSTM) have been employed in designing intrusion detection systems to address this issue. …”

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

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