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Showing 1 - 20 results of 1,765 for search '(((( develop box algorithm ) OR ( relevant data algorithm ))) OR ( data fitting algorithm ))', query time: 0.63s Refine Results
  1. 1
    Relevant Parameters.

    Relevant Parameters. by Dongyan Wang (195482)

    Published 2025
    “…By comparing the fitting performance of several methods, including ZOA-LSSVM, Genetic Algorithm (GA)-LSSVM, LSSVM, and Least Squares Regression (LSR), the effectiveness of ZOA-LSSVM is validated. …”
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  2. 2
    TOF dispersive data of the hard tissue-mimicking phantom fit with the KVFD model.

    TOF dispersive data of the hard tissue-mimicking phantom fit with the KVFD model. by Jotham Josephat Kimondo (19139409)

    Published 2025
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  3. 3
    Fitting flow of DAKM algorithm.

    Fitting flow of DAKM algorithm. by Xiaobing Chen (572034)

    Published 2025
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  4. 4
    Novel S-Box rendered by the suggested algorithm.

    Novel S-Box rendered by the suggested algorithm. by Nayeem Ahmad Khan (11727377)

    Published 2025
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  5. 5
    The relevant data file for this article.

    The relevant data file for this article. by Linsha Liu (20378293)

    Published 2024
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  6. 6
    Box plots of different algorithms.

    Box plots of different algorithms. by Kuiyuan Pan (21145338)

    Published 2025
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  7. 7
    Mean and standard deviation (SD) of MRI-derived myelin water fraction (MWF) values calculated using the data-driven mcT<sub>2</sub> approach and the conventional approach for the two mice groups and across six brain ROIs: cortex, medial corpus callosum (MCC), external corpus callosum (ECC), hippocampus (HIPP), thalamus, and striatum. All relevant data are available at data-driven-mcT2-cuprizone-validation GitHub repository and can be accessed at: https://github.com/NoamBenEliezer/data-driven-mcT2-cuprizone-validation.

    Mean and standard deviation (SD) of MRI-derived myelin water fraction (MWF) values calculated using the data-driven mcT<sub>2</sub> approach and the conventional approach for the t... by Noam Omer (21402801)

    Published 2025
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  8. 8
    Comparison of average fitting errors for the three algorithms.

    Comparison of average fitting errors for the three algorithms. by Xiaobing Chen (572034)

    Published 2025
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  9. 9
    Curve fitting of mean velocity versus frequency for the soft mimicking phantom, comparing experimental data with the theoretical KVFD model.

    Curve fitting of mean velocity versus frequency for the soft mimicking phantom, comparing experimental data with the theoretical KVFD model. by Jotham Josephat Kimondo (19139409)

    Published 2025
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  10. 10
    Curve fitting of mean velocity versus frequency for the hard mimicking phantom, comparing experimental data with the theoretical KVFD model.

    Curve fitting of mean velocity versus frequency for the hard mimicking phantom, comparing experimental data with the theoretical KVFD model. by Jotham Josephat Kimondo (19139409)

    Published 2025
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  11. 11
    Fitted density estimates under the clustering solution of the K⋅R model.

    Fitted density estimates under the clustering solution of the K⋅R model. by Koyel Majumdar (20416871)

    Published 2024
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  12. 12
    Comparison results of prediction model with single algorithm and combination algorithm.

    Comparison results of prediction model with single algorithm and combination algorithm. by Jiayuan Wang (3765376)

    Published 2025
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  13. 13
    Fitted density estimates under the K⋅R model on a simulated dataset.

    Fitted density estimates under the K⋅R model on a simulated dataset. by Koyel Majumdar (20416871)

    Published 2024
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  14. 14
    Comparison of experimental data from three different algorithms.

    Comparison of experimental data from three different algorithms. by Xiaobing Chen (572034)

    Published 2025
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  15. 15
    Relevant computed image data.

    Relevant computed image data. by Zhaoyu Ku (20660546)

    Published 2025
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  16. 16
    Fitness values of IRBMO vs. other binary algorithms.

    Fitness values of IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

    Published 2025
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  17. 17
    <b>Algorithmic Fitness: Fitness Influencers and Identity Construction on Tiktok</b><b> Data collection </b>

    <b>Algorithmic Fitness: Fitness Influencers and Identity Construction on Tiktok</b><b> Data collection </b> by Taylor Caruso (22272823)

    Published 2025
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  18. 18
    The KVFD model fits the dispersive data of the hard tissue-mimicking phantom across a frequency range of 0.1-1 Hz.

    The KVFD model fits the dispersive data of the hard tissue-mimicking phantom across a frequency range of 0.1-1 Hz. by Jotham Josephat Kimondo (19139409)

    Published 2025
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  19. 19
    The KVFD model fits the dispersive data of the soft tissue-mimicking phantom across a frequency range of 0.1–1 Hz.

    The KVFD model fits the dispersive data of the soft tissue-mimicking phantom across a frequency range of 0.1–1 Hz. by Jotham Josephat Kimondo (19139409)

    Published 2025
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  20. 20
    Comparison of execution time for the three algorithms.

    Comparison of execution time for the three algorithms. by Xiaobing Chen (572034)

    Published 2025
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