A radar plot illustrating the comparison of the classification accuracy, cost values, and fitness values for the hybrids of BEOSA when applied to some high-dimensional datasets usi... by Olaide N. Oyelade (14047002)

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A radar plot illustrating the comparison of the classification accuracy, cost values, and fitness values for the hybrids of BEOSA when applied to some medium-sized dimensional data... by Olaide N. Oyelade (14047002)

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A radar plot illustrating the comparison of the classification accuracy, cost values, and fitness values for the hybrids of BEOSA when applied to some small-sized dimensional datas... by Olaide N. Oyelade (14047002)

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Datasets and their properties. by Olaide N. Oyelade (14047002)

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Parameter settings. by Olaide N. Oyelade (14047002)

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Fig 4 - by Olaide N. Oyelade (14047002)

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Fig 7 - by Olaide N. Oyelade (14047002)

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Fig 2 - by Olaide N. Oyelade (14047002)

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An illustration and comparison of the fitness convergence curves for the Large-scale dataset (WaveformEW), medium-scale dataset (Zoo dataset), and Small-scale (Wine dataset) using... by Olaide N. Oyelade (14047002)

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An illustration and comparison of the cost convergence curves for the Large-scale dataset (WaveformEW), medium-scale dataset (Zoo dataset), and Small-scale (Wine dataset) using 50... by Olaide N. Oyelade (14047002)

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

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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DE algorithm flow. by Ling Zhao (111365)

“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”

Test results of different algorithms. by Ling Zhao (111365)

“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”

MSE for ILSTM algorithm in binary classification. by 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. …”

Illustration of the transformed binary images of normal, benign, and malignant samples into grayscale. by Tehnan I. A. Mohamed (16846175)

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)

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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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. …”