Sensitivity values of IRBMO vs. other binary algorithms. حسب Chenyi Zhu (9383370)

Specificity values of IRBMO vs. other binary algorithms. حسب Chenyi Zhu (9383370)

Fitness values of IRBMO vs. other binary algorithms. حسب Chenyi Zhu (9383370)

Number of features selected for IRBMO vs. other binary algorithms. حسب Chenyi Zhu (9383370)

Classification accuracy values of IRBMO vs. other binary algorithms. حسب Chenyi Zhu (9383370)

F-score values of IRBMO vs. other binary algorithms. حسب Chenyi Zhu (9383370)

Initial parameter settings for the optimization algorithms. حسب Doaa Sami Khafaga (21463870)

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

"…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"

Bar chart comparing the average fitness values of various feature selection algorithms. حسب Doaa Sami Khafaga (21463870)

Box plots with swarm overlays for six feature selection algorithms, annotated with mean and standard deviation values. حسب Doaa Sami Khafaga (21463870)

Line plots showing performance trends for six evaluation metrics across CNN combined with different bio-inspired optimization algorithms. حسب Doaa Sami Khafaga (21463870)

Correlation heatmap of performance scores among different feature selection algorithms: bOcOA, bPSO, bGWO, bFA, bGA, and bWAO. حسب Doaa Sami Khafaga (21463870)

Density distribution plot of performance metrics for various feature selection algorithms: bOcOA, bPSO, bGWO, bFA, bGA, and bWAO. حسب Doaa Sami Khafaga (21463870)

Homomorphic binary tree. حسب Jianhua He (341366)

The Pseudo-Code of the IRBMO Algorithm. حسب Chenyi Zhu (9383370)

"…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"

IRBMO vs. meta-heuristic algorithms boxplot. حسب Chenyi Zhu (9383370)

"…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"

IRBMO vs. feature selection algorithm boxplot. حسب Chenyi Zhu (9383370)

"…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"

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. …"