结合非线性回归方法，可以对回归结果进一步优化，得到更优的回归方程。
With the nonlinear regression method, results can be improved to get more optimal regression functions.
在此基础上，应用多元非线性回归方法得到了斜板桥最大支反力实用设计计算公式。
On this basis, the empirical computing formula of skewed-plate bridge maximum reaction for design is obtained using poly cell nonlinear regression method.
用非线性回归方法得出了水样不同处理方式下总磷间的经验关系式，并进行了验证。
The empirical relationship of the differences was obtained using nonlinear regression method and verified with the determined data.
根据试验数据，应用多元非线性回归方法建立了密度与摆放位置关系的数学模型，并讨论了改善烧结密度的措施。
Maths model is built up to show the relationship of density with locating place using multiple nonlinear regression analysis of experimental results.
同时考虑样地的随机效应、观测数据的时间序列相关性及不同初植密度的混合模型模拟精度比传统的非线性回归方法模拟精度高。
The precision of mixed model considering plot random effects, time series error autocorrelation and different plantation density at one time is better than that of ordinary regression analysis method.
采用非线性回归的方法，提出了该桥混凝土箱梁的温度梯度模式。
The mode of temperature gradient of this Bridges box girder is developed by the method of nonlinear regression.
本文将讨论综合运用非线性回归模型和时间序列分析的方法进行变形预报。
This article demonstrates that deformation forecast will be performed by a comprehensive method of non linear regression model combined with time series analysis.
对有限总体在不放回抽样的方法下，构造了一类非线性回归估计量，讨论了它的性质及其有关抽样误差．。
A kind of nonlinear regression estimator for limited Population is given and the quality and the sampling variance about is discussed.
仿真和实算结果表明，对于一大类线性和非线性回归模型，该方法给出的回归模型的参数估计效率的估计更接近模型参数估计效率的真值。
Simulation results and real measuring data calculations show that the precision estimation efficiency can be obtained by our method for a large class of linear and nonlinear regression models.
提出了一种基于分类技术的支持向量回归方法，解决数据分布未知、数学模型未知的非线性回归问题。
A support vector regression method based on classification is presented to solve the nonlinear regression problem with unknown data distribution and mathematical model.
介绍非线性回归和操作条件的非线性优化方法。
The non linear regression and non linear optimization methods for operating conditions were introduced.
数据拟合是数理统计学中的一个永恒话题，在实际工作中我们最常用的拟合方法是回归分析，其中包括线性回归和非线性回归。
Data smoothing is a perpetual topic in mathematical statistics. In practice we usually use regression to smooth data, including linear regression and nonlinear regression.
最后，利用验证数据对混合模型方法与传统的非线性回归模拟方法进行精度比较。
Finally, the precision of mixed models was compared with the precision of conventional nonlinear ordinary regression analysis method based on validation data.
最后，利用验证数据对混合模型方法与传统的非线性回归模拟方法进行精度比较。
Finally, the precision of mixed models was compared with the precision of conventional nonlinear ordinary regression analysis method based on validation data.
应用推荐