RESULTS: The fitting precision was compared by using mean relative error and grey absolute correlation degree as evaluation criterion.
结果：以平均相对偏差和灰色绝对关联度为评价标准进行拟合精度的比较。
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的空间格局和河道日径流量，多年年径流的模拟误差小于10%。
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.
用标准预测误差(%SEP)，平均预测误差(MPE)和平均相对误差(MRE)来评价其预测能力。
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，虽然策略库比较简单，但其预测的平均相对误差仅为1.73%。
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.
实验中得到了与实际更接近的平均流速估计，相对误差仅为5.62%，与滤波法的相对误差12.83%相比，准确性得到了一定的提高。
The relative error of annual mean evaporation is less than 4%.
年平均蒸发量相对误差小于4％。
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.
对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%。
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.
平均的相对误差在6%左右。说明本数据采集系统采集的数据有较高的可信性。
Scatter diagrams and the statistical criteria of relative error and mean square deviation were used to evaluate this model.
通过散点图以及相对误差、均方差两种统计学指标对该模型进行评价。
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）此模型预测结果的相对误差绝对值均值从PLS模型的3.92%，降低到了0.13%；
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的精度进行比较分析。
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的精度进行比较分析。
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