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中文摘要：
本文探讨了支持向量机方法在降雨一径流预测中的应用。该方法采用结构风险最小化准则。弥补了人工神经网络在预测应用中的不足，较好地解决了小样本，非线性、高维数和局部最小点等实际问题。并且本研究通过与人工神经网络预测方法、传统的回归分析预测方法比较研究．得出支持向量机能取得更高精度的降雨-径流预测值。
英文摘要：
This paper discussed the application of the support vector machine method in rainfall-runoff forecasting. The method used the principle of Structural Risk Minimization （SRM）. The support vector machine method made up the defective of Artificial Neural Network in forecast application. The model is very useful to solve the problem such as small sample, nonlinearity, high dimension, local minimization. Comparison was made between SVM methods with Artificial Neural Network and traditional regression analysis. The comparison results indicate that SVM method can obtain the high accuracy rainfall-runoff predicted value.
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