Search alternatives:
model optimization » codon optimization (Expand Search), global optimization (Expand Search), wolf optimization (Expand Search)
binary base » binary mask (Expand Search), ciliary base (Expand Search), binary image (Expand Search)
base model » based model (Expand Search), based models (Expand Search), game model (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), wolf optimization (Expand Search)
binary base » binary mask (Expand Search), ciliary base (Expand Search), binary image (Expand Search)
base model » based model (Expand Search), based models (Expand Search), game model (Expand Search)
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Comparison table of the proposed model.
Published 2024“…Moreover, among all the hyperparameter-optimized algorithms, adaboost algorithm outperformed all the other hyperparameter-optimized algorithms. …”
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Confusion matrix of ensemble model.
Published 2024“…Moreover, among all the hyperparameter-optimized algorithms, adaboost algorithm outperformed all the other hyperparameter-optimized algorithms. …”
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Flowchart scheme of the ML-based model.
Published 2024“…<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. …”
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ROC comparison of machine learning algorithm.
Published 2024“…Moreover, among all the hyperparameter-optimized algorithms, adaboost algorithm outperformed all the other hyperparameter-optimized algorithms. …”
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Results of machine learning algorithm.
Published 2024“…Moreover, among all the hyperparameter-optimized algorithms, adaboost algorithm outperformed all the other hyperparameter-optimized algorithms. …”
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Algorithm for generating hyperparameter.
Published 2024“…Moreover, among all the hyperparameter-optimized algorithms, adaboost algorithm outperformed all the other hyperparameter-optimized algorithms. …”
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Plan frame of the house.
Published 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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Ablation test results.
Published 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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Hyperparameter selection test.
Published 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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Multiple index test results of different methods.
Published 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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Backtracking strategy diagram.
Published 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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Comparison of differences in literature methods.
Published 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. …”