the first error model is based on root mean square error in normal direction of the transition curve .
该文推导了缓和曲线上任意点坐标的方差的加权平均值,来建立描述曲线元不确定性的模型。
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。
the correlation coefficients(r) and root mean square error of prediction(rmsep) were used as the model evaluation indices.
以预测集的预测相关系数(r),预测标準偏差(rmsep)作为模型评价指标。
the missing detect rate, false detect rate, correlation coefficient, and root mean square error are used to evaluate the algorithm.
并用漏检率、误检率、相关系数和均方根差对实验结果进行客观分析,验证了算法的有效性。