水资源与水工程学报2016，Vol.27Issue(1)：96-100,5.DOI:10.11705/j.issn.1672-643X.2016.01.17
模糊模式识别模型在古交矿区汾河支流水质评价中的应用
Application of fuzzy pattern recognition model in water quality assessment of Fenhe River tributary at Gujiao mining section
摘要
Abstract
Gujiao mining section in Fenhe River is a main recharge area of groundwater source of Taiyuan,and the pollution in the section is more serious.The tributaries in the section is one of several pollution sources.The paper applied the fuzzy pattern recognition model with the method of correlation coefficient to determine the index weights so as to assess the water quality of the tributaries of Gujiao mining section in Fenhe River comprehensively.The results showed that the level characteristic value of water quality of nine tributaries is between 1 and 2,and the water quality of the section is better.The water quality level in Dachuan,Shizi and Tianchi river is approximate level Ⅰ,and that of other 6 tributaries is level Ⅱ.The evaluation result is reasonable and objective,which can provide academic reference for the pollution control and comprehensive management of water resources in Gujiao section of Fenhe river.关键词
水质评价/模糊识别模型/古交矿区/汾河支流Key words
water quality assessment/fuzzy recognition model/Gujiao mining section/Fen River tributary分类
资源环境引用本文复制引用
陈姣艳,李洪建,严俊霞,杨永刚..模糊模式识别模型在古交矿区汾河支流水质评价中的应用[J].水资源与水工程学报,2016,27(1):96-100,5.基金项目
山西省科技厅软科学项目(2014041016-1) （2014041016-1）
国家国际科技合作专项项目(2012DFA20770) （2012DFA20770）
