本文对目前地下水环境质量预测的研究方法进行了系统总结，详细地阐述了统计学习理论研究的基本问题及主要内容。

In this thesis, the current groundwater quality prediction methods were systematically summarized and the essential issues and main contents of statistical learning theory are elaborated.

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其次，认真研究了统计学习理论的主要内容和SVM算法的基本原理，并且就SVM的多种多类别分类算法分别加以讨论。

Secondly, the text studies the Statistical Learning Theory(STL) and Support Vector Machine(SVM)theory seriously, discusses multi-category classification algorithms of SVM.

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首先概述了本文研究内容的基础—统计学习理论与支持向量机方法，为本文后续的研究方向和内容进行了铺垫。

This paper's basic concepts of Statistical Learning Theory and SVM are summarized firstly, which are the groundwork of next research works.

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