The support vector machines theory is shown to have excellent performance compared with other non-linear regression, such as neural networks.
支持向量机（SVM）回归理论与神经网络等非线性回归理论相比具有许多独特的优点。
The models were developed and provided a reasonable equation for biomass, production and glucose. And parameters were obtained by using non-linear regression techniques.
建立了该菌株分批发酵合成红谷霉素的菌体生长、产物合成和葡萄糖消耗的动力学模型，并对模型参数进行了非线性回归。
Methods:Power model of non-linear regression was adopted to fit the curve of incidence of malaria, which result is contrast with the same model came from curve estimation method.
方法：对疟疾发病率曲线进行非线性过程的幂函数拟合，并与用曲线参数估计法的幂函数拟合结果进行对比。
Posted the following code is for a 19 input variables, an output variable in case of non-linear regression designed, if applied to other situations, simply change your codec function.
以下贴出的代码是为一个19输入变量，1个输出变量情况下的非线性回归而设计的，如果要应用于其它情况，只需改动编解码函数即可。
Based on the data observed, 34 regression models on the morphological variables and biomass of the seedlings were set up using linear, multilinear and non linear regression.
根据实测的数据，采用一元线性、多元线性和非线性回归进行拟合，得到34个红海榄幼苗主要形态因子和生物量的回归模型。
The non linear regression and non linear optimization methods for operating conditions were introduced.
介绍非线性回归和操作条件的非线性优化方法。
This article demonstrates that deformation forecast will be performed by a comprehensive method of non linear regression model combined with time series analysis.
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。
Because of complex deformation on slope, it is difficult to handle the regular pattern of deformation on slope by applying non linear regression model accurately.
边坡变形的复杂性决定了运用非线性回归模型很难准确解决边坡变形规律。
Non - Linear Regression Model?
非线性回归模型NLRM ？
For non-linear problem, the forecasting technique of pre-classification and later regression was proposed, based on the classification approach of Support Vector Machine (SVM).
针对非线性问题，提出了基于支持向量机分类基础的先分类、再回归的预测方法。
With the excellence in complex and non-linear information processing, artificial neural network is fitter for the forecasting of fetal weight than traditional regression methods.
对复杂的、非线性信息处理有其独特的优势。在预测胎儿体重这一领域，人工神经网络的方法比传统的回归分析法有着更大的优势。
With the excellence in complex and non-linear information processing, artificial neural network is fitter for the forecasting of fetal weight than traditional regression methods.
对复杂的、非线性信息处理有其独特的优势。在预测胎儿体重这一领域，人工神经网络的方法比传统的回归分析法有着更大的优势。
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