Showing 121 - 140 results of 3,041 for search '(( significant progress decrease ) OR ( significant ((shape decrease) OR (step decrease)) ))', query time: 0.49s Refine Results
  1. 121
  2. 122

    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.…”
  3. 123

    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.…”
  4. 124

    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.…”
  5. 125

    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.…”
  6. 126

    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.…”
  7. 127

    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.…”
  8. 128

    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.…”
  9. 129

    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.…”
  10. 130

    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.…”
  11. 131

    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.…”
  12. 132

    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.…”
  13. 133

    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.…”
  14. 134

    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.…”
  15. 135

    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.…”
  16. 136

    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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