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Showing 21 - 30 results of 30 for search '(((("elements model algorithm") OR ("elements mges algorithm"))) OR ("effects learning algorithm"))', query time: 0.54s Refine Results
  1. 21
    Influence of Shape Parameters on the Compressive Performance of the Specimens.

    Influence of Shape Parameters on the Compressive Performance of the Specimens. by Nan Ru (9594384)

    Published 2025
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  2. 22
    Schematic diagram of the extension of vertices of large and small polygons.

    Schematic diagram of the extension of vertices of large and small polygons. by Nan Ru (9594384)

    Published 2025
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  3. 23
    Specimen for the splitting test.

    Specimen for the splitting test. by Nan Ru (9594384)

    Published 2025
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  4. 24
    The influence of angularity on the splitting resistance performance of the specimens.

    The influence of angularity on the splitting resistance performance of the specimens. by Nan Ru (9594384)

    Published 2025
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  5. 25
    Example Diagram.

    Example Diagram. by Nan Ru (9594384)

    Published 2025
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  6. 26
    Influence of Shape Parameters on the Splitting Resistance Performance of the Specimens.

    Influence of Shape Parameters on the Splitting Resistance Performance of the Specimens. by Nan Ru (9594384)

    Published 2025
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  7. 27
    Aggregate Measurement Image in IPP.

    Aggregate Measurement Image in IPP. by Nan Ru (9594384)

    Published 2025
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  8. 28
    Influence of the Roundness Ratio on the Compressive Performance of the Specimens.

    Influence of the Roundness Ratio on the Compressive Performance of the Specimens. by Nan Ru (9594384)

    Published 2025
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  9. 29
    Internal changes of the specimen of 0.89 to 1.

    Internal changes of the specimen of 0.89 to 1. by Nan Ru (9594384)

    Published 2025
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  10. 30
    A machine learning approach of predicting high potential archers by means of physical fitness indicators

    A machine learning approach of predicting high potential archers by means of physical fitness indicators by Rabiu Muazu Musa (6172304)

    Published 2019
    “…<div><p><i>k</i>-nearest neighbour (<i>k</i>-NN) has been shown to be an effective learning algorithm for classification and prediction. …”
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