Showing 141 - 160 results of 2,317 for search '(( significant shape decrease ) OR ( significant ((step decrease) OR (greater decrease)) ))', query time: 0.55s Refine Results
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  6. 146

    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.…”
  7. 147

    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.…”
  8. 148

    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.…”
  9. 149

    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.…”
  10. 150

    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.…”
  11. 151

    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.…”
  12. 152

    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.…”
  13. 153

    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.…”
  14. 154

    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.…”
  15. 155

    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.…”
  16. 156

    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.…”
  17. 157

    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.…”
  18. 158

    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.…”
  19. 159

    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.…”
  20. 160

    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.…”