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Showing 1 - 20 results of 435 for search '(( element data algorithm ) OR ((( data processing algorithm ) OR ( deep machine algorithm ))))*', query time: 0.12s Refine Results
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    Efficient Dynamic Cost Scheduling Algorithm for Data Batch Processing by Al Sadawi, Alia

    Published 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. …”
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    doctoralThesis
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    A Survey of Data Clustering Techniques by Sobeh, Salma

    Published 2023
    Subjects: “…Cluster analysis -- Data processing…”
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    masterThesis
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    Leveraging Machine and Deep Learning Algorithms for hERG Blocker Prediction by Syed Mohammad (21075689)

    Published 2025
    “…Predicting the binding capability of molecules with hERG channels is expected to reduce the burden of cardiotoxicity testing in drug evaluation. The application of machine learning (ML) and deep learning (DL) models in the field of toxicity has gained burgeoning interest. …”
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    Efficient Dynamic Cost Scheduling Algorithm for Financial Data Supply Chain by Al Sadawi, Alia

    Published 2021
    “…An iterative dynamic scheduling algorithm (DCSDBP) was developed to address the data batching process. …”
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    article
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    An efficient approach for textual data classification using deep learning by Abdullah Alqahtani (7128143)

    Published 2022
    “…This paper employs machine and deep learning techniques to classify textual data. …”
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    Genetic and heuristic algorithms for regrouping service sites. (c2000) by Tabbara, Hiba

    Published 2000
    Subjects: “…Genetic algorithms -- Data processing…”
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    masterThesis
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    On the steiner walk problem. (c2009) by Maarouf, Amina

    Published 2009
    Subjects: “…Euclidean algorithm -- Data processing…”
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    masterThesis
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    Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks by Najam Us Sahar Riyaz (22927843)

    Published 2025
    “…Drawing on more than fifteen harmonized datasets that span pyrimidines, ionic liquids, graphene oxides, and additional compound families, we benchmark traditional algorithms, such as artificial neural networks, support vector machines, k-nearest neighbors, random forests, against advanced graph-based and deep architectures including three-level directed message-passing neural networks, 2D3DMol-CIC, and graph convolutional networks. …”
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