基于模糊模式识别的支持向量机的回归预测方法

尝试把最近发展起来的支持向量机引入水文预测中,建立了支持向量机水文回归预测模型,为小样本情况下水文预测提供一种行之有效的可选择的方法。在此基础上,为了更好地处理水文系统中广泛存在的不确定、模糊信息,进一步把模糊模式识别理论引入支持向量机,提出一种模糊模式识别核函数。该核函数具有更明确合理的物理意义。冰凌预测实例表明了SVM水文回归预测方法及模糊模式识别核函数的有效性和可行性。

A SVM regress forecasting method based on the fuzzy recognition theory

This paper first introduces the support vector machine(SVM) regression forecasting method into hydrological forecasting.Further,based on the fuzzy recognition theory proposed by Prof.Chen Shou-yu,a new kind of kernel function of SVM is proposed in the paper.The kernel function has a more reasonable physical significance.At the end,the results of a study case show that the SVM regression hydrological forecasting method and the kernel function of fuzzy pattern recognition is reasonable and feasible.