基于SVR的PFC微观参数辅助标定方法研究
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温晨,黄敏,邱贤阳,黄帅
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Auxilliary Calibration Method for Microscopic Parameters of PFC Based on SVR
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Chen WEN,Min HUANG,Xianyang QIU,Shuai HUANG
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表7 BP神经网络参数标定结果
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Table 7 Calibration results of BP neural network parameters
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次数 | 微观参数(预测) | 宏观参数(数值模拟) | 误差百分比/% |
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GPa | | | MPa | MPa | /(°) | GPa | | MPa | MPa | / | | | | |
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1 | 8.03 | 2.26 | 0.511 | 36.5 | 21.6 | 38.5 | 9.62 | 0.302 | 38.1 | 8.7 | 4.4 | 8.5 | 36.7 | 45.4 | 66.5 | 2 | 6.46 | 1.47 | 0.553 | 41.5 | 18.5 | 49.6 | 8.14 | 0.218 | 33.0 | 5.6 | 5.9 | 3.0 | 1.4 | 26.0 | 6.5 | 3 | 6.24 | 1.86 | 0.660 | 41.1 | 19.3 | 53.6 | 8.43 | 0.253 | 34.4 | 6.2 | 5.6 | 5.0 | 14.5 | 31.3 | 19.6 | 4 | 6.12 | 1.50 | 0.532 | 41.0 | 20.3 | 56.9 | 8.51 | 0.216 | 31.5 | 5.8 | 5.4 | 4.0 | 0.5 | 20.2 | 11.1 | 5 | 6.82 | 1.92 | 0.659 | 44.6 | 16.6 | 59.6 | 9.15 | 0.256 | 26.8 | 4.5 | 6.0 | 3.2 | 15.8 | 2.3 | 13.5 | 6 | 6.81 | 1.67 | 0.602 | 41.0 | 18.9 | 52.4 | 9.21 | 0.229 | 30.5 | 5.8 | 5.3 | 3.8 | 3.6 | 16.4 | 11.9 | 7 | 5.85 | 1.63 | 0.581 | 42.6 | 16.6 | 55.5 | 8.11 | 0.225 | 27.0 | 4.8 | 5.6 | 8.6 | 1.8 | 3.1 | 6.9 | 8 | 6.35 | 1.62 | 0.637 | 46.5 | 18.0 | 55.9 | 8.61 | 0.216 | 27.7 | 5.0 | 5.5 | 5.7 | 2.9 | 2.3 | 4.6 | 待标定参数 | | 8.87 | 0.221 | 26.2 | 5.2 | 5.0 | |
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