改进的GM(1,1)模型在小南海泉涌泉量预测中的应用

The Application of the Improved Grey Model in Xiaonanhai Spring Flow Prediction

灰色系统模型在贫信息、小样本的非线性系统建模中具有明显优势,适合对时间序列较短时的需水量进行预测。针对基本灰色预测模型背景值构造不合理,及未充分利用新信息的缺点,采用重构背景值和等维递补原理对基本GM(1,1)模型进行改进,并利用改进模型对安阳市小南海泉的涌泉量进行拟合和预测,结果表明,改进模型预测精度更高。

Grey system model has obvious advantages in building poor-information and small-sample nonlinear model,which makes it suitable to predict water demand of short time series.But the model has deficiencies：construction of the basic model＇s background value is unreasonable; new information is not completely used.So this article adopt reconstructing background value and equi-dimensional supplement theory to improve the basic GM（1,1） grey model,then use the improved model to fit and predict the spring flow of Xiaonanhai spring,the result shows that the improved model have higher predicting precision.