水资源污染负荷强度的灰色有效性预测模型及其应用

Construction of Prediction Model and Its Application of Water Pollution Load Intensity Based on Grey Effectiveness

水资源污染负荷强度预测是水污染防治的关键环节。基于灰色系统理论,构建了水资源污染负荷强度的GM(1,1)模型、Verhulst模型和SCGM(1,1)c模型,并利用预测有效度计算各单预测模型的权重,进而建立水资源污染负荷强度的灰色GM-Verhulst-SCGM组合预测模型,在此基础上,选取2004-2013年期间工业单位产值化学需氧量排放量历史数据进行模型拟合,利用其2014-2016年数据进行模型检验。研究发现,灰色组合预测模型呈现出更低的预测误差,符合水资源污染负荷强度高精度预测需求;而通过对水资源污染负荷强度实证预测发现,其负荷强度整体上呈逐步削弱的态势,但可能会出现其高速下降向稳步趋缓转变的速率"拐点",预示着水污染防治将由"浅水区"向"深水区"的转变。

The prediction of water pollution load intensity is the key link of water pollution control. Hence, the GM(1,1) model, Verhulst model and SCGM(1,1)c model of water pollution load intensity were constructed based on grey system theory, and then the weight of these predictive models was calculated by predicting effectiveness method, and the GM-Verhulst-SCGM grey combination prediction model could be constructed. Moreover, the historical data of chemical oxygen demand (COD) emissions per unit of industrial output value was applied to model fitting from 2004 to 2013, and the data from 2014 to 2016 was applied to model test. The results showed that: the prediction error of grey combination model was lower, so it met the need of accurate prediction of water pollution load intensity. Meanwhile, empirical analysis found that the water pollution load intensity was gradually declined, but there might be an “inflection point” could emerge. It meant that the rate of water pollution load intensity descent will gradually slow down form high speed, and the water pollution control would be changed from “shallow water area” to “deep water area”.