Showing 121 - 140 results of 2,814 for search '(( significantly predicted decrease ) OR ( significant ((shape decrease) OR (nn decrease)) ))', query time: 0.72s Refine Results
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  4. 124

    Generated spline library. by Zhe Hu (787283)

    Published 2025
    “…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”
  5. 125

    Correlation coefficient matrix. by Zhe Hu (787283)

    Published 2025
    “…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”
  6. 126

    RMSE versus learning rate. by Zhe Hu (787283)

    Published 2025
    “…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”
  7. 127

    RMSE versus training parameters. by Zhe Hu (787283)

    Published 2025
    “…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”
  8. 128

    Assembly process of machine recognition form. by Zhe Hu (787283)

    Published 2025
    “…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”
  9. 129

    Process of steel truss incremental launching. by Zhe Hu (787283)

    Published 2025
    “…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”
  10. 130

    CGAN and AutoML stacking device. by Zhe Hu (787283)

    Published 2025
    “…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”
  11. 131

    U-wave estimates versus R-matrix noise variance. by Zhe Hu (787283)

    Published 2025
    “…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”
  12. 132

    Sliding window process. by Zhe Hu (787283)

    Published 2025
    “…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”
  13. 133

    Assembly error angle of a single spline. by Zhe Hu (787283)

    Published 2025
    “…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”
  14. 134

    Original record form of error matrix. by Zhe Hu (787283)

    Published 2025
    “…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”
  15. 135

    Form for machine recognition. by Zhe Hu (787283)

    Published 2025
    “…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”
  16. 136

    RMSE versus architectural parameters. by Zhe Hu (787283)

    Published 2025
    “…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”
  17. 137

    Kalman process. by Zhe Hu (787283)

    Published 2025
    “…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”
  18. 138

    Attention mechanism. by Zhe Hu (787283)

    Published 2025
    “…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”
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