基于灰色广义回归神经网络的工业废水排放量预测

Forecast of industrial waste water volume based on GM-GRNN

将GM(1,1)预测模型与广义回归神经网络结合起来,构建了一种新型串联灰色神经网络预测方法,有效地将灰色系统的贫乏数据建模和神经网络特有的非线性适应性信息处理能力相融合,充分提取历史数据及相关因素数据包含的信息,建立精度较高的预测模型。通过对工业废水排放量实例预测,结果表明该方法是有效可行的。

A new series grey ANN forecast model was proposed by unified the GM （1,1） with GRNN, effectively integrated the Grey System that can be constructed the forecast model with poor information and the GRNN was capable of processing non-linear adaptable information, so the new model had both of their advantages. It be fully considered the historic data and correlation factor data, the forecasting results were high precision. An example of industrial waste water volume was forcasted, the results have shown that this method was effective and feasible.