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Showing 1 - 20 results of 90 for search '(( binary data points optimization algorithm ) OR ( binary first design optimization algorithm ))', query time: 0.60s Refine Results
  1. 1
    Illustration of the transformed binary images of normal, benign, and malignant samples into grayscale.

    Illustration of the transformed binary images of normal, benign, and malignant samples into grayscale. by Tehnan I. A. Mohamed (16846175)

    Published 2023
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  2. 2
    RMSE on the test data when fitting (logistic) quadratic models to binary data across increasing measurement error values .

    RMSE on the test data when fitting (logistic) quadratic models to binary data across increasing measurement error values . by Jakub Stoklosa (3315042)

    Published 2023
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  3. 3
    Binary leaf image rotated anti-clock wise from the origin degree to 40<sup><i>o</i></sup>, 80<sup><i>o</i></sup>, 120<sup><i>o</i></sup>, and 160<sup><i>o</i></sup> from left to right respectively to verify rotation invariance with their corresponding curve-fitted data.

    Binary leaf image rotated anti-clock wise from the origin degree to 40<sup><i>o</i></sup>, 80<sup><i>o</i></sup>, 120<sup><i>o</i></sup>, and 160<sup><i>o</i></sup> from left to ri... by Ali Ahmed (2567584)

    Published 2020
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  4. 4
    Homomorphic binary tree.

    Homomorphic binary tree. by Jianhua He (341366)

    Published 2024
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  5. 5
    Design and implementation of the Multiple Criteria Decision Making (MCDM) algorithm for predicting the severity of COVID-19.

    Design and implementation of the Multiple Criteria Decision Making (MCDM) algorithm for predicting the severity of COVID-19. by Jiaqing Luo (10975030)

    Published 2021
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  6. 6
    MCLP_quantum_annealer_V0.5

    MCLP_quantum_annealer_V0.5 by Anonymous Anonymous (4854526)

    Published 2025
    “…The application of quantum computing to solve the maximum coverage location problem presents numerous challenges in areas like problem transformation, quantum sampling solutions, and spatial relationship verification. This paper first proposes the QUBO-MCLP algorithm workflow and designs the Transformation Operator for Inequality Constraints Considering the Capacity of Accessible Providers (TOICCAP), which accounts for the scale of accessible supply points. …”
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  7. 7
    Datasets and their properties.

    Datasets and their properties. by Olaide N. Oyelade (14047002)

    Published 2023
    “…The binary Ebola optimization search algorithm (BEOSA) is applied for the level-1 mutation, while the simulated annealing (SA) and firefly (FFA) algorithms are investigated for the level-2 optimizer. …”
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  8. 8
    Parameter settings.

    Parameter settings. by Olaide N. Oyelade (14047002)

    Published 2023
    “…The binary Ebola optimization search algorithm (BEOSA) is applied for the level-1 mutation, while the simulated annealing (SA) and firefly (FFA) algorithms are investigated for the level-2 optimizer. …”
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  9. 9
    Microsoft excel file containing exhaustive list of Abbreviated-Injury Scale codes used to generate binary variables encoding the presence or absence of injury to various body regions/organ systems.

    Microsoft excel file containing exhaustive list of Abbreviated-Injury Scale codes used to generate binary variables encoding the presence or absence of injury to various body regio... by Michael D. Cobler-Lichter (22492930)

    Published 2025
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  10. 10
    Parameter settings of the comparison algorithms.

    Parameter settings of the comparison algorithms. by Ying Li (38224)

    Published 2024
    “…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”
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  11. 11
    Fig 1 -

    Fig 1 - by Jakub Stoklosa (3315042)

    Published 2023
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  12. 12
    Latent state estimations for experimental data with no stressors.

    Latent state estimations for experimental data with no stressors. by Samiul Alam (18563323)

    Published 2024
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  13. 13
    Latent state estimations for experimental data with interruptions.

    Latent state estimations for experimental data with interruptions. by Samiul Alam (18563323)

    Published 2024
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  14. 14
    Latent state estimations for experimental data with time limit.

    Latent state estimations for experimental data with time limit. by Samiul Alam (18563323)

    Published 2024
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  15. 15
    Schematic representation of semi-automated algorithm for organoids analyzing.

    Schematic representation of semi-automated algorithm for organoids analyzing. by Anna Demchenko (18449439)

    Published 2025
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  16. 16
    Comparison in terms of the sensitivity.

    Comparison in terms of the sensitivity. by Ying Li (38224)

    Published 2024
    “…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”
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  17. 17
    Parameter sensitivity of BIMGO.

    Parameter sensitivity of BIMGO. by Ying Li (38224)

    Published 2024
    “…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”
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  18. 18
    Details of the medical datasets.

    Details of the medical datasets. by Ying Li (38224)

    Published 2024
    “…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”
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  19. 19
    The flowchart of IMGO.

    The flowchart of IMGO. by Ying Li (38224)

    Published 2024
    “…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”
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  20. 20
    Comparison in terms of the selected features.

    Comparison in terms of the selected features. by Ying Li (38224)

    Published 2024
    “…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”
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