该方法基于半模糊核聚类算法挖掘不同类别之间的衔接和离散信息，设计树型支持向量机的树型结构，克服其差错积累问题。
The method mines information on overlap between classes, designs the tree structure and overcomes the misclassification of tree-structured SVMs based on the semi-fuzzy kernel clustering algorithm.
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.
针对图像在获取和传输过程中易受各种噪声污染的事实，为了提高支持向量机对噪声图像的分割性能，提出了模糊权重支持向量机。
In order to improve the segmentation performance of images corrupted by impulse noise and Gaussian noise, fuzzy weighted support vector machine is proposed.
针对图像在获取和传输过程中易受各种噪声污染的事实，为了提高支持向量机对噪声图像的分割性能，提出了模糊权重支持向量机。
In order to improve the segmentation performance of images corrupted by impulse noise and Gaussian noise, fuzzy weighted support vector machine is proposed.
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