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Showing 1 - 20 results of 153 for search '(( binary mainly driven optimization algorithm ) OR ( primary data set optimization algorithm ))', query time: 0.61s Refine Results
  1. 1
    The parameter settings of the RF algorithm after parameter optimization.

    The parameter settings of the RF algorithm after parameter optimization. by Xini Fang (20861990)

    Published 2025
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  2. 2
    Parameter settings for algorithms.

    Parameter settings for algorithms. by Guangwei Liu (181992)

    Published 2024
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  3. 3
    Parameter settings for algorithms.

    Parameter settings for algorithms. by Guangwei Liu (181992)

    Published 2024
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  4. 4
    Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things

    Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things by Ashok Kumar K (21441108)

    Published 2025
    “…Hence, Binary Black Widow Optimization Algorithm (BBWOA) is proposed in this manuscript to improve the BRBPNN classifier that detects intrusion precisely. …”
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  5. 5
    Features selected by optimization algorithms.

    Features selected by optimization algorithms. by Afnan M. Alhassan (18349378)

    Published 2024
    “…After the image has been pre-processed, it is segmented using the Thresholding Level set approach. Next, we propose a hybrid chaotic sand cat optimization technique, together with the Remora Optimization Algorithm (ROA) for feature selection. …”
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  6. 6
    Pseudocode of artificial dragonfly algorithm.

    Pseudocode of artificial dragonfly algorithm. by Ghassan Ahmed Ali (17041488)

    Published 2023
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  7. 7
    Principle of the SVM algorithm.

    Principle of the SVM algorithm. by Anfeng Zhu (17817144)

    Published 2024
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  8. 8
    The Hopfield artificial neural network algorithm.

    The Hopfield artificial neural network algorithm. by Ghassan Ahmed Ali (17041488)

    Published 2023
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  9. 9
    Parameter settings.

    Parameter settings. by Guangwei Liu (181992)

    Published 2023
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  10. 10
    Data_Sheet_1_Genetic Algorithms for Optimized Diagnosis of Alzheimer’s Disease and Frontotemporal Dementia Using Fluorodeoxyglucose Positron Emission Tomography Imaging.PDF

    Data_Sheet_1_Genetic Algorithms for Optimized Diagnosis of Alzheimer’s Disease and Frontotemporal Dementia Using Fluorodeoxyglucose Positron Emission Tomography Imaging.PDF by Josefa Díaz-Álvarez (5572427)

    Published 2022
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  11. 11
    Data_Sheet_2_Genetic Algorithms for Optimized Diagnosis of Alzheimer’s Disease and Frontotemporal Dementia Using Fluorodeoxyglucose Positron Emission Tomography Imaging.PDF

    Data_Sheet_2_Genetic Algorithms for Optimized Diagnosis of Alzheimer’s Disease and Frontotemporal Dementia Using Fluorodeoxyglucose Positron Emission Tomography Imaging.PDF by Josefa Díaz-Álvarez (5572427)

    Published 2022
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  12. 12
    FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology

    FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

    Published 2024
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  13. 13
    FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology

    FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

    Published 2024
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  14. 14
    FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology

    FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

    Published 2024
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  15. 15
    FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology

    FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

    Published 2024
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  16. 16
    FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology

    FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

    Published 2024
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  17. 17
    FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology

    FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

    Published 2024
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  18. 18
    FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology

    FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

    Published 2024
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  19. 19
    Variable importance of features included in the gradient boosting machine learning (XGB) algorithm for predicting postinduction hypotension.

    Variable importance of features included in the gradient boosting machine learning (XGB) algorithm for predicting postinduction hypotension. by Manabu Yoshimura (11040049)

    Published 2022
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  20. 20
    Patient characteristics across different healthcare settings.

    Patient characteristics across different healthcare settings. by Geert-Jan Geersing (331049)

    Published 2022
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