يعرض 1 - 20 نتائج من 316 نتيجة بحث عن '(( primary data model optimization algorithm ) OR ( primary data wolf optimization algorithm ))', وقت الاستعلام: 1.23s تنقيح النتائج
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    Evaluation metrics of the models’ performance. حسب Guangwei Liu (181992)

    منشور في 2024
    "…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …"
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    S1 Data - حسب Guangwei Liu (181992)

    منشور في 2024
    "…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …"
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    Parameter settings for algorithms. حسب Guangwei Liu (181992)

    منشور في 2024
    "…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …"
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    Parameter settings for algorithms. حسب Guangwei Liu (181992)

    منشور في 2024
    "…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …"
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    Average runtime of different algorithms. حسب Guangwei Liu (181992)

    منشور في 2024
    "…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …"
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    Average runtime of different algorithms. حسب Guangwei Liu (181992)

    منشور في 2024
    "…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …"
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    Flowchart of GJO-GWO algorithm. حسب Guangwei Liu (181992)

    منشور في 2024
    "…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …"
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    Detailed information of benchmark functions. حسب Guangwei Liu (181992)

    منشور في 2024
    "…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …"
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    Detailed information of datasets. حسب Guangwei Liu (181992)

    منشور في 2024
    "…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …"
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    Friedman test results. حسب Guangwei Liu (181992)

    منشور في 2024
    "…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …"
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    Average number of selected features. حسب Guangwei Liu (181992)

    منشور في 2024
    "…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …"
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    Wilcoxon rank sum test results. حسب Guangwei Liu (181992)

    منشور في 2024
    "…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …"
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    Wilcoxon rank sum test results. حسب Guangwei Liu (181992)

    منشور في 2024
    "…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …"
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    Average number of selected features. حسب Guangwei Liu (181992)

    منشور في 2024
    "…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …"
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    Features selected by optimization algorithms. حسب Afnan M. Alhassan (18349378)

    منشور في 2024
    "…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …"
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