基于灰色动态模型群法的河流水质预测研究

Prediction of River Water Quality Based on Gray Dynamic Model Group

水质预测是水环境规划、评价和管理工作的基础。依据灰色系统理论 ,构造了一个由 6个 GM(1,1)模型组成的灰色动态模型群 ,并运用该模型群对淮河干流枯水期氨氮浓度变化趋势进行了预测分析 ,得到令人满意的结果。研究表明 ,灰色动态模型群法能够充分利用近期水质资料信息预测未来水质变化趋势 ;以模型群统计平均值作为最终预测值 ,避免了单一灰色模型容易利用不稳定信息的缺陷 ,使得预测精度更加准确 。

Water quality prediction is the basis of water environmental planning, evaluation and management. A gray dynamic model group is put forward made up of six simple gray models. Then the model group is used to predict the trend of concentration of NH 3-N in the Huaihe river during dry season. The result shows that the gray dynamic model group can make full use of the recent information about water quality to predict the future trend of water quality, and that prediction result stemming from gray dynamic model group is more accurate and reliable than that of a simple gray model.