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Showing 1 - 20 results of 1,065 for search '(((( element network algorithm ) OR ( relevant data algorithm ))) OR ( math modeling algorithm ))', query time: 0.36s Refine Results
  1. 1
    Efficiency analysis of FuzzyMath.

    Efficiency analysis of FuzzyMath. by Yanyan Dong (1304145)

    Published 2025
    “…The research difficulties are addressed by integrating the Fuzzy logic and mathematical model called the FuzzyMath approach. The FuzzyMath concept understands the industrial economic details and predicts financial performance with maximum recognition accuracy. …”
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  2. 2
    FuzzyMath excellence analysis.

    FuzzyMath excellence analysis. by Yanyan Dong (1304145)

    Published 2025
    “…The research difficulties are addressed by integrating the Fuzzy logic and mathematical model called the FuzzyMath approach. The FuzzyMath concept understands the industrial economic details and predicts financial performance with maximum recognition accuracy. …”
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  3. 3
    The relevant data file for this article.

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

    Published 2024
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  4. 4
    Supporting data for "Toward Self-Improving and Sustainable Large Language Models"

    Supporting data for "Toward Self-Improving and Sustainable Large Language Models" by Qintong Li (11173806)

    Published 2025
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  5. 5
    Coefficient table of determined variables (reading, maths and science).

    Coefficient table of determined variables (reading, maths and science). by Bilal Baris Alkan (21647275)

    Published 2025
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  6. 6
    Relevant computed image data.

    Relevant computed image data. by Zhaoyu Ku (20660546)

    Published 2025
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  7. 7
    Overall Structure of FuzzyMath-based financial efficiency prediction.

    Overall Structure of FuzzyMath-based financial efficiency prediction. by Yanyan Dong (1304145)

    Published 2025
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  8. 8
    Summary of relevant works.

    Summary of relevant works. by Bashir Olaniyi Sadiq (22478011)

    Published 2025
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  9. 9
    Most Important Variables in Reading(a), Science(b) and Math(c) Section.

    Most Important Variables in Reading(a), Science(b) and Math(c) Section. by Bilal Baris Alkan (21647275)

    Published 2025
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  10. 10
    The relevant code in the manuscript can be found in the supporting information data file.

    The relevant code in the manuscript can be found in the supporting information data file. by Xini Fang (20861990)

    Published 2025
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  11. 11
    Model-relevant variable data for external patients.

    Model-relevant variable data for external patients. by Lei Gao (6566)

    Published 2025
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  12. 12
    Computational Domain: The computational domain was discretized using conformal tetrahedral elements, resulting in a total of 926K elements.

    Computational Domain: The computational domain was discretized using conformal tetrahedral elements, resulting in a total of 926K elements. by Martina Bukač (20161460)

    Published 2024
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  13. 13
    ML algorithms in cyber security.

    ML algorithms in cyber security. by Abdullah Asım Yılmaz (20715311)

    Published 2025
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  14. 14
    Relevant data underlying the findings described in manuscript.

    Relevant data underlying the findings described in manuscript. by Lin Qi (128224)

    Published 2025
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  15. 15
    Data generation algorithm.

    Data generation algorithm. by Aluwani Ramalata (21262977)

    Published 2025
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  16. 16
    Relevant Parameters.

    Relevant Parameters. by Dongyan Wang (195482)

    Published 2025
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  17. 17
    <b>Robot_gripper_design</b>

    <b>Robot_gripper_design</b> by Ma Haohao (19780875)

    Published 2024
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  18. 18
    Data Sheet 1_Algorithmic esthetics meets human intuition: the synergy of innovation and relevance shapes sustained attention.pdf

    Data Sheet 1_Algorithmic esthetics meets human intuition: the synergy of innovation and relevance shapes sustained attention.pdf by Wen Guan (5612195)

    Published 2025
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  19. 19
    Comparison of the EODA algorithm with existing algorithms in terms of recall.

    Comparison of the EODA algorithm with existing algorithms in terms of recall. by Sunil Kumar (102321)

    Published 2025
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  20. 20
    Comparison of the EODA algorithm with existing algorithms in terms of precision.

    Comparison of the EODA algorithm with existing algorithms in terms of precision. by Sunil Kumar (102321)

    Published 2025
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