中文摘要：

函数拟合是一种重要的数据挖掘技术．在本文中，我们将一个改进的高斯混合模型应用于水位变化规律的研究中，以便更好的做出水位预报．以洞庭湖流域安乡站点为例，首先将其近十年来的水位数据进行数据预处理，得出每年的满足损失函数极小化的类高斯混合模型，再构造超定线性方程组并且利用最小二乘法求得各年对应的权重，从而得到一个加权模型，最后对此模型进行了合理性检验，并提出了改进结果．

英文摘要：

Function fitting is an important data mining technique. In this paper, the modified Gauss type mixed model is applied to the study of the changing pattern of the water level in order to make accurate prediction of the water level. Firstly, we make a pretreatment of the ten years data of the water level and establish a Gauss --like mixed model which satisfies the smallest loss function via curve fit. Then, we construct an overdeter- mined linear equations and use the least square method to obtain the corresponding weight. Finally, we get a Weighted model and examine the rationality of the model and make some improvements.