يعرض 21 - 40 نتائج من 472 نتيجة بحث عن '(( elements method algorithm ) OR ((( data groups algorithm ) OR ( data modeling algorithm ))))', وقت الاستعلام: 0.14s تنقيح النتائج
  1. 21

    Parallel physical optimization algorithms for allocating data to multicomputer nodes حسب Mansour, Nashat

    منشور في 1994
    "…Three parallel physical optimization algorithms for allocating irregular data to multicomputer nodes are presented. …"
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    article
  2. 22

    Physical optimization algorithms for mapping data to distributed-memory multiprocessors حسب Mansour, Nashat

    منشور في 1992
    "…We present three parallel physical optimization algorithms for mapping data to distributed-memory multiprocessors, concentrating on irregular loosely synchronous problems. …"
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    masterThesis
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    Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data حسب Arfan Ahmed (17541309)

    منشور في 2023
    "…</p><h3>Research Design & Methods</h3><p dir="ltr">The study aimed to investigate performance of AI models in estimating BGL among diabetic patients using non-invasive wearable devices data An open-source dataset was used which provided BGL readings, diabetic status (Diabetic or non-diabetic), heart rate, Blood oxygen level (SPO2), Diastolic Blood pressure, Systolic Blood Pressure, Body temperature, Sweating, and Shivering for 13 participants by age group taken from WDs. …"
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    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. …"
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    article
  7. 27

    DG-Means – A Superior Greedy Algorithm for Clustering Distributed Data حسب Assaf, Ali

    منشور في 2022
    "…In this work, we present DG-means, which is a greedy algorithm that performs on distributed sets of data. …"
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    masterThesis
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    Multilayer Reversible Data Hiding Based on the Difference Expansion Method Using Multilevel Thresholding of Host Images Based on the Slime Mould Algorithm حسب Abu Zitar, Raed

    منشور في 2022
    "…Researchers have scrutinized data hiding schemes in recent years. Data hiding in standard images works well, but does not provide satisfactory results in distortion-sensitive medical, military, or forensic images. …"
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    A Survey of Data Clustering Techniques حسب Sobeh, Salma

    منشور في 2023
    "…Clustering, an unsupervised learning technique, aims to identify a specific number of clusters to effectively categorize the data through data grouping. Hence, clustering is related to many fields and is used in various applications that deal with large datasets. …"
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    masterThesis
  15. 35

    Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks حسب Najam Us Sahar Riyaz (22927843)

    منشور في 2025
    "…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R<sup>2</sup> = 0.05 to 0.99 in a representative thiophene set. …"
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    Using genetic algorithms to optimize software quality estimation models حسب Azar, Danielle

    منشور في 2004
    "…In the first approach, we assume the existence of several models, and we use a genetic algorithm to combine them, and adapt them to a given data set. …"
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    masterThesis
  19. 39

    Second-order conic programming for data envelopment analysis models حسب Mourad, Nahia

    منشور في 2022
    "…This paper constructs a second-order conic optimization problem unifying several DEA models. Moreover, it presents an algorithm that solves the former problem, and provides a MATLAB function associated with it. …"
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    The automation of the development of classification models and improvement of model quality using feature engineering techniques حسب Sjoerd Boeschoten (17347045)

    منشور في 2023
    "…In this article, we propose a framework that combines feature engineering techniques such as data imputation, transformation, and class balancing to compare the performance of different prediction models and select the best final model based on predefined parameters. …"