应用灰色模糊马尔科夫链预测海河水质变化趋势  

Water quality prediction of Haihe River using grey-fuzzy-markov chain model

作　　者：于慧[1] 孙宝盛[1] 李亚楠[1] 张燕[1] 齐庚申[1] 

机构地区：[1]天津大学环境科学与工程学院,天津300072

出　　处：《中国环境科学》2014年第3期810-816,共7页China Environmental Science

基　　金：天津市自然科学基金重点资助项目(07JCZDJC02100)

摘　　要：灰色 GM（1,1）模型在水质预测中得到了较为广泛的运用,但其存在灰色偏差与抗干扰能力弱的局限性,针对这一问题,将马尔科夫链理论与模糊集合理论引入灰色GM（1,1）预测模型,并应用该模型对海河三岔口断面的DO、CODMn和NH3-N 3项指标2012-2016年的浓度变化趋势进行预测.结果表明,2004-2016年,DO及NH3-N浓度大致呈上升趋势,预计2016年分别可达9.15,1.47mg/L；CODMn浓度呈下降趋势,预计2016年可达3.91mg/L.以2012年的数据做验证,灰色模糊马尔科夫链模型的预测精度最高,可作为科学的水质预测方法.The GM（1,1） model has been widely used in the prediction of water quality. But it had the disadvantages of grey bias and weak anti-jamming capability. To solve this problem, the markov chain theory and fuzzy classification were introduced into the grey forecasting model and a new method named the Grey-Fuzzy-Markov Chain Model was proposed. In this paper, the tendency changes of DO,CODMn and NH3-N’s concentration were predicted in Haihe River from 2012 to 2016. The results showed that from 2004 to 2016 the concentration of DO and NH3-N would increase to 9.15 and 1.47mg/L respectively in 2016. Meanwhile the CODMn would decrease to 3.91mg/L in 2016. The concentration of DO,CODMn and NH3-N in 2012 were forecasted to check the precision of this model. The precision of the Grey-Fuzzy-Markov model was better than the GM（1,1） model and it would be a scientific method for the prediction of water quality.

关 键 词：GM(1 1)模型 模糊分类 马尔科夫模型 

分 类 号：X824[环境科学与工程—环境工程]