بدائل البحث:
based optimization » whale optimization (توسيع البحث)
binary basic » binary mask (توسيع البحث)
basic based » music based (توسيع البحث), basic gases (توسيع البحث)
binary a » binary _ (توسيع البحث), binary b (توسيع البحث), hilary a (توسيع البحث)
a global » _ global (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
binary basic » binary mask (توسيع البحث)
basic based » music based (توسيع البحث), basic gases (توسيع البحث)
binary a » binary _ (توسيع البحث), binary b (توسيع البحث), hilary a (توسيع البحث)
a global » _ global (توسيع البحث)
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21
Best optimizer results of Decision tree.
منشور في 2024"…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. …"
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22
Best optimizer results of Extra tree.
منشور في 2024"…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. …"
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23
Best optimizer results of Random Forest.
منشور في 2024"…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. …"
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24
Best optimizer result for Extra tree.
منشور في 2024"…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. …"
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25
IRBMO vs. meta-heuristic algorithms boxplot.
منشور في 2025"…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …"
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26
IRBMO vs. feature selection algorithm boxplot.
منشور في 2025"…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …"
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27
Plan frame of the house.
منشور في 2025"…<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. …"
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28
Ablation test results.
منشور في 2025"…<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. …"
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29
Hyperparameter selection test.
منشور في 2025"…<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. …"
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30
Multiple index test results of different methods.
منشور في 2025"…<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. …"
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31
Backtracking strategy diagram.
منشور في 2025"…<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. …"
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32
Comparison of differences in literature methods.
منشور في 2025"…<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. …"
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33
New building interior space layout model flow.
منشور في 2025"…<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. …"
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34
Schematic of iteration process of IDE-IIGA.
منشور في 2025"…<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. …"
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35
Schematic diagram of IGA chromosome coding.
منشور في 2025"…<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. …"
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36
Hyperparameters of the LSTM Model.
منشور في 2025"…The AD-PSO-Guided WOA overcomes limitations of conventional optimization algorithms, such as premature convergence by balancing global search (exploration) and local refinement (exploitation). …"
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37
The AD-PSO-Guided WOA LSTM framework.
منشور في 2025"…The AD-PSO-Guided WOA overcomes limitations of conventional optimization algorithms, such as premature convergence by balancing global search (exploration) and local refinement (exploitation). …"
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38
Prediction results of individual models.
منشور في 2025"…The AD-PSO-Guided WOA overcomes limitations of conventional optimization algorithms, such as premature convergence by balancing global search (exploration) and local refinement (exploitation). …"
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39
Results of KNN.
منشور في 2024"…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. …"
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40
Comparison of key techniques in their literature.
منشور في 2024"…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. …"