يعرض 1 - 20 نتائج من 399 نتيجة بحث عن '(((( data processing algorithm ) OR ( novel learning algorithm ))) OR ( element data algorithm ))', وقت الاستعلام: 0.14s تنقيح النتائج
  1. 1

    Efficient Dynamic Cost Scheduling Algorithm for Data Batch Processing حسب Al Sadawi, Alia

    منشور في 2016
    "…A Master of Science thesis in Engineering Systems Management by Alia Al Sadawi entitled, "Efficient Dynamic Cost Scheduling Algorithm for Data Batch Process," submitted in May 2016. …"
    احصل على النص الكامل
    doctoralThesis
  2. 2

    Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering حسب Abu Zitar, Raed

    منشور في 2022
    "…This paper proposes a new data clustering method using the advantages of metaheuristic (MH) optimization algorithms. …"
  3. 3
  4. 4

    Efficient Dynamic Cost Scheduling Algorithm for Financial Data Supply Chain حسب Al Sadawi, Alia

    منشور في 2021
    "…An iterative dynamic scheduling algorithm (DCSDBP) was developed to address the data batching process. …"
    احصل على النص الكامل
    article
  5. 5
  6. 6

    On the steiner walk problem. (c2009) حسب Maarouf, Amina

    منشور في 2009
    الموضوعات: "…Euclidean algorithm -- Data processing…"
    احصل على النص الكامل
    احصل على النص الكامل
    masterThesis
  7. 7
  8. 8
  9. 9

    Nonlinear analysis of shell structures using image processing and machine learning حسب M.S. Nashed (16392961)

    منشور في 2023
    "…The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. …"
  10. 10
  11. 11
  12. 12
  13. 13
  14. 14
  15. 15
  16. 16
  17. 17
  18. 18
  19. 19

    A Novel Partitioned Random Forest Method-Based Facial Emotion Recognition حسب Hanif Heidari (22467148)

    منشور في 2025
    "…The proposed method divides multiple regions (different data lengths) into the feature space, allowing the algorithm to learn more complex decision boundaries. …"
  20. 20