求翻译：近年来，学者们为了进一步提高SVM分类性能，提出了支持向量分类器集成方法，其应用结果表明：与单一SVM相比，SVM集成可以获得更好或者至少同等的分类能力[7]。常用的SVM集成算法是基于投票策略的，无法评价各个子分类器输出信息对于最终判决的重要程度，而基于模糊积分的SVM集成则是通过模糊积分对不确定信息的测量，把非线性的客观现象与SVM输出重要性的主观评价结合起来，改进基于投票策略SVM集成方法中的缺陷，使集成分类器具有更强的泛化能力是什么意思？

In recent years, scholars in order to further improve the performance of SVM classifiers, support vector classifiers proposed integrated approach, its application results show that: compared with the single SVM, SVM can better integrate or at least the same classification ability [7]. SVM algorithm

In recent years, scholars in order to further enhance SVM classification performance, presented a support vector classifier integrated methods, their application results show that, compared with the single SVM SVM integration can obtain better or at least equal the classification capacity [ 7 ]. Com

In recent years, scholars in order to further improve the SVM classification performance, presented support vector classifiers integration method, apply the results indicate that the single compared to the SVM, SVM integration can get better or at least the same level of classification ability [7].