The support vector machine (SVM) is an algorithm based on structure risk minimizing principle and high generalization ability.

支持向量机(SVM)是一种基于结构风险最小化原理，具有很好推广性能的学习算法。

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The high generalization ability of Support Vector Machine (SVM) makes it especially suitable for the classification of high-dimension data such as term-document.

支持向量机(SVM)高度的泛化能力使它特别适用于高维数据例如文档的分类。

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In the calculation example, the real data were used for the dynamic modeling of the load, and the results show that the load model is accurate and has high generalization ability.

算例中利用实测数据进行负荷动态建模，结果表明可得到精度和泛化能力都较高的负荷模型，在电力负荷建模方面具有广泛的应用价值。

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