最后在模拟测试之下，利用最大概似估计法求得各参数的误差、均方根误差、参数之上下界限以及涵盖。

Simulation results show that the maximum likelihood estimates perform well in most cases in terms of the mean bias, errors in the root mean square and the coverage rate.

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除了用单行数值比较法外，还计算了重组和数学模型之间的归一化均方根偏差、归一化平均偏差和最大偏差。

Besides a comparison of the characteristic line, the normalized mean square root error, the normalized mean error, and the maximum deviation are calculated and discussed.

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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 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.

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