中文摘要：

支持向量机能够成功的解决分类和回归问题,但是训练数据都是精确的。如果支持向量机的训练集中含有模糊信息,即训练集中的输入训练样本点为模糊数,那么支持向量机将无能为力。基于此,在可能性测度理论和模糊机会约束规划的基础上,建立了模糊v-支持向量机模型,并将该方法应用于某病的诊断中,实验结果验证了该方法的有效性。

英文摘要：

Support vector machines have been very successful in classification and regression problems,but the training data are non-fuzzy.There are lots of fuzzy information in the objective world,and if there are fuzzy information in the training set of support vector machines（SVMs）,that is the input of training point is fuzzy number,then traditional SVMs will fail.Fuzzy v-support vector machine based on possibility measure and fuzzy chance constrained programming is proposed.Finally,fuzzy v-support vector machine is applied to the coronary ill diagnose,and the experimental result shows that the proposed model is promising.