介绍了支持向量机分类和回归算法，将其应用于梁结构的损伤诊断中。
This paper introduces the support vector classification and regression algorithms, which are applied to the structure damage identification.
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.
结果表明SORR优于标准的支持向量机回归估计算法。
The experimental results show that the proposed SORR algorithm is better than the normal regression estimation algorithm of SVM.
目前，如何设计快速有效的回归估计算法仍然是支持向量机实际应用中的问题之一。
Now, how to design fast and efficient SVM algorithms applied to regression estimation becomes a great challenge in practical applications of support vector machine.
该文对用于回归估计的标准支持向量机(SVM)加以改进，提出了一种新的用于回归估计的支持向量机学习算法。
Based on the traditional support vector machine (SVM) for regression, a new learning algorithm of the improved SVM for regression is presented in this paper.
该文对用于回归估计的标准支持向量机(SVM)加以改进，提出了一种新的用于回归估计的支持向量机学习算法。
Based on the traditional support vector machine (SVM) for regression, a new learning algorithm of the improved SVM for regression is presented in this paper.
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