بدائل البحث:
simulation algorithm » segmentation algorithm (توسيع البحث), maximization algorithm (توسيع البحث), selection algorithm (توسيع البحث)
design optimization » bayesian optimization (توسيع البحث)
process simulation » process optimization (توسيع البحث)
binary complex » ternary complex (توسيع البحث), snare complex (توسيع البحث)
binary a » binary _ (توسيع البحث), binary b (توسيع البحث), hilary a (توسيع البحث)
a design » _ design (توسيع البحث), co design (توسيع البحث)
simulation algorithm » segmentation algorithm (توسيع البحث), maximization algorithm (توسيع البحث), selection algorithm (توسيع البحث)
design optimization » bayesian optimization (توسيع البحث)
process simulation » process optimization (توسيع البحث)
binary complex » ternary complex (توسيع البحث), snare complex (توسيع البحث)
binary a » binary _ (توسيع البحث), binary b (توسيع البحث), hilary a (توسيع البحث)
a design » _ design (توسيع البحث), co design (توسيع البحث)
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21
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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22
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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23
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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24
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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25
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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26
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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27
Results of machine learning algorithm.
منشور في 2024"…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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28
Datasets and their properties.
منشور في 2023"…The approach used in this study designed a sub-population selective mechanism that dynamically assigns individuals to a 2-level optimization process. …"
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29
Parameter settings.
منشور في 2023"…The approach used in this study designed a sub-population selective mechanism that dynamically assigns individuals to a 2-level optimization process. …"
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30
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36
ROC comparison of machine learning algorithm.
منشور في 2024"…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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37
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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38
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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39
Best optimizer results of Lightbgm.
منشور في 2024"…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
Best optimizer results of Adaboost.
منشور في 2024"…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. …"