灰色系统动态模型群GM(1,1)在秦淮河水质预测中的应用

Application of Grey System Dynamic Model Group GM(1,1) in Water Quality Prediction of Qinhuai River

为了较为准确预测水质,基于灰色系统理论建立灰色系统动态模型群,采用对数变换的方式对原始数据进行光滑处理,借以减弱数据波动带来的不利影响,是对常规灰色系统动态模型的改进。结合秦淮河上游源头句容河2011～2016年高锰酸盐指数,运用灰色系统动态模型群对2017年高锰酸盐指数进行预测。预测结果表明误差在1.24%以内,表明灰色系统动态模型群GM(1,1)用于水质预测较为准确。该模型可应用于南京市水质预测,对水环境管理具有指导意义。

In order to predict water quality more accurately,this paper builds a grey system dynamic model group based on grey system theory.The original data was smoothed using logarithmic form to reduce the influence of data uncertainties,which is an improvement over the conventional gray system dynamic model.This paper combines the permanganate index of Jurong River in the upper reaches of Qinhuaihe River in 2011-2016,and uses the grey system dynamic model group to predict the permanganate index in 2017.The prediction results show that the error is within 1.24%,indicating that the grey system dynamic model group is considerably accurate for water quality prediction.The model can be applied to the prediction of water quality in Nanjing which will provide guiding significance for water environment management.