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Showing 21 - 40 results of 146 for search '(( primary aim based optimization algorithm ) OR ( binary case based optimization algorithm ))', query time: 0.54s Refine Results
  1. 21
    Boxplots in EV tests.

    Boxplots in EV tests. by Mouncef El Marghichi (17328361)

    Published 2023
    “…The GBO minimizes a cost with the aim of selecting the optimal candidate for updating the SOH through a memory-fading forgetting factor. …”
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  2. 22
    GBO parameters for HEV.

    GBO parameters for HEV. by Mouncef El Marghichi (17328361)

    Published 2023
    “…The GBO minimizes a cost with the aim of selecting the optimal candidate for updating the SOH through a memory-fading forgetting factor. …”
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  3. 23
    GBO parameters for HEV.

    GBO parameters for HEV. by Mouncef El Marghichi (17328361)

    Published 2023
    “…The GBO minimizes a cost with the aim of selecting the optimal candidate for updating the SOH through a memory-fading forgetting factor. …”
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  4. 24
    MEAN and MAX error in (%).

    MEAN and MAX error in (%). by Mouncef El Marghichi (17328361)

    Published 2023
    “…The GBO minimizes a cost with the aim of selecting the optimal candidate for updating the SOH through a memory-fading forgetting factor. …”
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  5. 25
    <i>x</i><sub><i>j</i></sub>, and <i>y</i><sub><i>j</i></sub> variables for HEV tests.

    <i>x</i><sub><i>j</i></sub>, and <i>y</i><sub><i>j</i></sub> variables for HEV tests. by Mouncef El Marghichi (17328361)

    Published 2023
    “…The GBO minimizes a cost with the aim of selecting the optimal candidate for updating the SOH through a memory-fading forgetting factor. …”
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  6. 26
    The duration of a single cycle, measured in ms.

    The duration of a single cycle, measured in ms. by Mouncef El Marghichi (17328361)

    Published 2023
    “…The GBO minimizes a cost with the aim of selecting the optimal candidate for updating the SOH through a memory-fading forgetting factor. …”
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  7. 27
    GBO framework used to estimate the battery SOH.

    GBO framework used to estimate the battery SOH. by Mouncef El Marghichi (17328361)

    Published 2023
    “…The GBO minimizes a cost with the aim of selecting the optimal candidate for updating the SOH through a memory-fading forgetting factor. …”
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  8. 28
    #EV PDF (drive cycle durations).

    #EV PDF (drive cycle durations). by Mouncef El Marghichi (17328361)

    Published 2023
    “…The GBO minimizes a cost with the aim of selecting the optimal candidate for updating the SOH through a memory-fading forgetting factor. …”
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  9. 29
    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
    “…In the realm of medicinal chemistry, the primary objective is to swiftly optimize a multitude of chemical properties of a set of compounds to yield a clinical candidate poised for clinical trials. …”
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  10. 30
    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
    “…In the realm of medicinal chemistry, the primary objective is to swiftly optimize a multitude of chemical properties of a set of compounds to yield a clinical candidate poised for clinical trials. …”
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  11. 31
    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
    “…In the realm of medicinal chemistry, the primary objective is to swiftly optimize a multitude of chemical properties of a set of compounds to yield a clinical candidate poised for clinical trials. …”
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  12. 32
    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
    “…In the realm of medicinal chemistry, the primary objective is to swiftly optimize a multitude of chemical properties of a set of compounds to yield a clinical candidate poised for clinical trials. …”
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  13. 33
    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
    “…In the realm of medicinal chemistry, the primary objective is to swiftly optimize a multitude of chemical properties of a set of compounds to yield a clinical candidate poised for clinical trials. …”
    Save to List
    Saved in:
  14. 34
    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
    “…In the realm of medicinal chemistry, the primary objective is to swiftly optimize a multitude of chemical properties of a set of compounds to yield a clinical candidate poised for clinical trials. …”
    Save to List
    Saved in:
  15. 35
    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
    “…In the realm of medicinal chemistry, the primary objective is to swiftly optimize a multitude of chemical properties of a set of compounds to yield a clinical candidate poised for clinical trials. …”
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  16. 36
    Image_1_The prognostic role of an optimal machine learning model based on clinical available indicators in HCC patients.TIF

    Image_1_The prognostic role of an optimal machine learning model based on clinical available indicators in HCC patients.TIF by Xiaoying Lou (9700261)

    Published 2024
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  17. 37
    Image_2_The prognostic role of an optimal machine learning model based on clinical available indicators in HCC patients.TIF

    Image_2_The prognostic role of an optimal machine learning model based on clinical available indicators in HCC patients.TIF by Xiaoying Lou (9700261)

    Published 2024
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  18. 38
    Random forest model performs better than support vector machine algorithms and when it primarily uses spontaneous photopic ERG of 60-s duration in humans.

    Random forest model performs better than support vector machine algorithms and when it primarily uses spontaneous photopic ERG of 60-s duration in humans. by Ramsés Noguez Imm (6658637)

    Published 2023
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  19. 39
    Distributions of model parameters mirror differentially expressed ion channel genes.

    Distributions of model parameters mirror differentially expressed ion channel genes. by Daniele Linaro (227790)

    Published 2022
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  20. 40
    UK Biobank data wrangling statistics and results.

    UK Biobank data wrangling statistics and results. by Simeone Marino (81051)

    Published 2020
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