• The numerical experiment results show that the mean forecast relative error is 1.73% even with a simple strategies library.

    数值实验显示虽然策略比较简单,但其预测平均相对误差1.73%。

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  • The mean blood velocity was estimated using the proposed method with a relative error of 5.62%, which demonstrated improved accuracy compared to 12.83% by using the high-pass filtering method.

    实验中得到了实际更接近平均流速估计相对误差仅为5.62%,与滤波法相对误差12.83%相比,准确性得到了一定的提高。

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  • RESULTS: The fitting precision was compared by using mean relative error and grey absolute correlation degree as evaluation criterion.

    结果平均相对偏差灰色绝对关联度评价标准进行拟合精度比较

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  • The relative error of annual mean evaporation is less than 4%.

    平均蒸发量相对误差小于4%。

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  • The root mean square relative error, mean absolute relative error and maximize absolute relative error of SVM model generalization performance are 1.06%, 0.96% and 1.16%, respectively.

    SVM多元非线性回归泛化性能进行测试,其均方根相对误差为1.06%,平均绝对相对误差为0.96%,最大绝对相对误差为1.16%。

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  • The standard error of prediction (% SEP), the mean prediction error (MPE) and the mean relative error (MRE) were utilized to evaluate the prediction ability of the BP-ANN.

    标准预测误差(%SEP),平均预测误差(MPE)平均相对误差(MRE)评价预测能力

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  • The mean value of the relative error between experimental data and theoretical data is about 6%, which indicates that the data from the acquisition system has better reliability.

    平均相对误差在6%左右。明本数据采集系统采集数据较高可信性

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  • Scatter diagrams and the statistical criteria of relative error and mean square deviation were used to evaluate this model.

    通过散点以及相对误差均方差两种统计学指标模型进行评价

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  • The results indicate:(1)the mean absolute value of relative error of the prediction results of this model has been reduced at 0.13% (the original is 3.92% in the PLS model);

    研究结果:(1模型预测结果相对误差绝对值均值PLS模型3.92%,降低到了0.13%;

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  • Coefficient determination, absolute bias, relative absolute bias, root mean square error and relative root mean square error were employed to evaluate the precision of different model systems.

    采用确定系数绝对误差相对绝对误差、均方根误差、相对均方根误差等模型评价指标对不同模型系统精度进行比较分析。

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  • The modelled spatial patterns of surface temperature and daily runoff are in well agreement with the observatio with the mean relative error less than 10%.

    模型能合理反演地表温度空间格局河道径流量,多年年径流模拟误差小于10%。

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  • The modelled spatial patterns of surface temperature and daily runoff are in well agreement with the observatio with the mean relative error less than 10%.

    模型能合理反演地表温度空间格局河道径流量,多年年径流模拟误差小于10%。

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