离差最大化结合BP神经网络评价烟叶化学品质
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张勇刚, 任志广, 徐志强, 刘建国, 张晓兵, 刘化冰, 夏琛, 程昌合
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Chemical Quality Evaluation of Flue-Cured Tobacco Based on Maximization of Deviation and BP Neural Network
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Zhang Yonggang, Ren Zhiguang, Xu Zhiqiang, Liu Jianguo, Zhang Xiaobing, Liu Huabing, Xia Chen, Cheng Changhe
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表6 预测集数据的预测误差
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Table 6 Prediction error of testing samples
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样品编号 Sample number | 实测值 Measured value | 预测值 Predicted value | 绝对误差 Absolute error | 相对误差 Relative error (%) | 1 | 0.5397 | 0.5378 | 0.0019 | 0.3520 | 2 | 0.4771 | 0.4840 | 0.0069 | 1.4462 | 3 | 0.4721 | 0.4702 | 0.0019 | 0.4025 | 4 | 0.6333 | 0.6239 | 0.0094 | 1.4843 | 5 | 0.6463 | 0.6489 | 0.0026 | 0.4023 | 6 | 0.7056 | 0.6916 | 0.0140 | 1.9841 | 7 | 0.3329 | 0.3373 | 0.0044 | 1.3217 | 8 | 0.6001 | 0.6035 | 0.0034 | 0.5666 | 9 | 0.5013 | 0.5063 | 0.0050 | 0.9974 | 10 | 0.4387 | 0.4396 | 0.0009 | 0.2052 | 11 | 0.6129 | 0.6240 | 0.0111 | 1.8111 | 12 | 0.6345 | 0.6374 | 0.0029 | 0.4571 | 13 | 0.4571 | 0.4582 | 0.0011 | 0.2406 | 14 | 0.6387 | 0.6322 | 0.0065 | 1.0177 | 15 | 0.6864 | 0.6920 | 0.0056 | 0.8159 | 16 | 0.6968 | 0.7008 | 0.0040 | 0.5741 | 17 | 0.5305 | 0.5355 | 0.0050 | 0.9425 | 18 | 0.4662 | 0.4610 | 0.0052 | 1.1154 | 19 | 0.6168 | 0.6148 | 0.0020 | 0.3243 | 20 | 0.3110 | 0.3196 | 0.0086 | 2.7653 | 21 | 0.6696 | 0.6689 | 0.0007 | 0.1045 | 22 | 0.3652 | 0.3641 | 0.0011 | 0.3012 | 23 | 0.8294 | 0.8305 | 0.0011 | 0.1326 | 24 | 0.6416 | 0.6459 | 0.0043 | 0.6702 |
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