摘要
鉴于当前水污染评价受臆断或数据噪声影响而导致评价结果失真,提出了超限学习机(RF)算法,对辽河沈阳段水污染进行评价。结果表明,研究区水体中DO、COD、NH、TP、FO和TN含量分别属于Ⅲ、Ⅳ、Ⅲ、Ⅳ、Ⅲ、Ⅱ级;评价结果显示,2003和2007~2010年属于重度污染,2000~2002年属于轻度污染,2004~2006年属于中度污染。
In view of the fact that the current water quality evaluation is distorted by subjective assumptions or data noise,in this paper,the application of extreme learning machine（ ELM） algorithm is proposed to assessment the water pollution in Liaohe River in Shenyang section.The results indicate that DO,COD,NH,TP,and TN belonged to Ⅲ,Ⅳ,Ⅲ,Ⅳ and Ⅱ.The assessments results showed 2003 and 2007 ~ 2010 belong to severe pollution,2000 ~ 2002 belongs to light pollution,2004 ~ 2006 belongs to moderate pollution.
作者
王树才
WANG Shu - cai(Beipiao City Water Resource Office, Beipiao 122100, Liaoning, China)
出处
《水利科技与经济》
2017年第10期47-50,共4页
Water Conservancy Science and Technology and Economy
关键词
ELM
水污染
评价
ELM
water pollution
evaluation
