通过线性规划技术和采用尺度函数作为核函数来实现支持向量回归模型。
Using linear programming technique and scaling kernel function, the support vector regression model was obtained.
同时对广泛的支持向量回归模型、优化支持向量模型的泛化能力和运算速度等方面进行讨论。
The generalization of the support vector regression model, the optimization of the generalization capacity, and the training speed are discussed.
采用支持向量回归在线辨识算法作为建模方法建立被控对象的逆模型。
Online identification algorithm of support vector regression is used to build the inverse model for the plant.
将改进的支持向量回归机与B -样条网络相结合，提出了一种建立回归曲线模型的新算法。
A new algorithm for modeling regression curve is put forward in the paper, it combines B-spline network with improved support vector regression.
给出带有模糊决策的模糊机会约束规划模型，在此基础上，研究模糊线性支持向量分类机(算法)和模糊线性支持向量回归机(算法)。
Proposed the model of fuzzy chance constrained programming with fuzzy decision, and did some research on fuzzy linear support vector regression (algorithm) on this base.
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.
针对这一问题，提出了支持向量回归多参数的同时调节模型。
To solve this problem, we propose a simultaneous tuning model for multiple parameters of SVR.
针对这一问题，提出了支持向量回归多参数的同时调节模型。
To solve this problem, we propose a simultaneous tuning model for multiple parameters of SVR.
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