研究基于模糊系数规划的模糊支持向量分类机。
Research on the fuzzy SVMs based on fuzzy coefficient programming.
成功解决了光滑支持向量分类机的收敛上界问题。
Therefore, the problem of upper bound of convergence was successfully solved for SSVM.
论文研究模糊支持向量分类机在冠心病诊断中的应用。
In this paper, we have studied on applying fuzzy support vector classification to coronary heart diagnose.
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.
提出依存关系规则与统计方法相结合，实现了基于依存关系与支持向量机的问题分类机制。
The results show that the feature extraction method using SVM based on dependency relations can get high classification accuracy.
结合粗糙集的属性约简和支持向量机的分类机理，提出了一种混合算法。
In this paper we present a novel hybrid algorithm based on attribute reduction of RS and classification principles of SVM.
集的属性约简和支持向量机的分类机理，提出了一种混合算法。
This article advanced a admixture arithmetic based on rough sets theory and via support vector machines.
集的属性约简和支持向量机的分类机理，提出了一种混合算法。
This article advanced a admixture arithmetic based on rough sets theory and via support vector machines.
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