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... حسب 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... حسب 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... حسب Olaide N. Oyelade (14047002)

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Fig 2 - حسب 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... حسب 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... حسب Olaide N. Oyelade (14047002)

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One advantage of our algorithm is that it is not binary in nature. حسب Yong Kuk Kim (13955214)

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

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DE algorithm flow. حسب 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. حسب 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. …"

Flowchart scheme of the ML-based model. حسب Noshaba Qasmi (20405009)

"…<b>I)</b> Testing data consisting of 20% of the entire dataset. <b>J)</b> Optimization of hyperparameter tuning. <b>K)</b> Algorithm selection from all models. …"

SHAP analysis mean value. حسب Balraj Preet Kaur (20370832)

"…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. 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. …"

Optimization of tracking parameters based on <i>P</i>_<i>swap</i>. حسب Benjamin Gallois (10131683)

Design and implementation of the Multiple Criteria Decision Making (MCDM) algorithm for predicting the severity of COVID-19. حسب Jiaqing Luo (10975030)

"…<p>(A). The MCDM algorithm-Stage 1. Preprocessing, this stage is the process of refining the collected raw data to eliminate noise, including correlation analysis and feature selection based on P values. …"

Medium-scale dataset comparative analysis using fitness and cost values for population size 50 and 100. حسب Olaide N. Oyelade (14047002)

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Small-scale dataset comparative analysis using fitness and cost values for population sizes 50 and 100. حسب Olaide N. Oyelade (14047002)

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Large-scale dataset comparative analysis using fitness and cost values for population sizes 50 and 100. حسب Olaide N. Oyelade (14047002)

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Algorithm for generating hyperparameter. حسب Balraj Preet Kaur (20370832)

"…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. 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. …"

Results of machine learning algorithm. حسب Balraj Preet Kaur (20370832)

"…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. 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. …"

ROC comparison of machine learning algorithm. حسب Balraj Preet Kaur (20370832)

"…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. 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. …"