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首页> 外文会议>2013 Fifth Conference on Measuring Technology and Mechatronics Automation. >Application of Fuzzy C-means Clustering for Assessing Rural Surface Water Quality in Lianyungang City
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Application of Fuzzy C-means Clustering for Assessing Rural Surface Water Quality in Lianyungang City

机译：模糊C均值聚类在连云港市农村地表水水质评价中的应用

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摘要

Surface water quality in rural areas usually has a great variation in China and is hard to charaterize by classical statistic methods. In this paper, a fuzzy c-means clustering method is used to classify and assess rural surface water quality based on the monitoring data from 33 typical stations in 23 rural rivers and 4 reservoirs in Lianyungang city. The results show that the 33 monitoring stations can be classified into 3 clusters in terms of water quality. The first cluster consists of 27 stations and most of their water quality indexes are nearly at or better than the national Grade II standards, while the second and third clusters respectively contain 5 and 1 stations, and their indexes of ammonia nitrogen and petroleum are at or worse than the national Grade V standards, and the index values in the third cluster generally exceed those in the second cluster. Thus, the overall quality of rural surface water in study area remains good, but there also exist some river sections contaminated with ammonia nitrogen and petroleum. Therefore, it is very necessary to establish water quality safety and risk assessment system for ensuring water supplies for production and daily life.
机译：在中国，农村地区的地表水水质通常变化很大，很难用经典的统计方法来表征。本文基于连云港市23条乡村河流和4个水库的33个典型站的监测数据，采用模糊c均值聚类方法对农村地表水水质进行分类和评估。结果表明，根据水质，可以将33个监测站分为3个类。第一组包含27个站，其大部分水质指数接近或优于国家二级标准，而第二组和第三组分别包含5个站和1个站，其氨氮和石油指数等于或高于比国家V级标准差，并且第三组中的指标值通常超过第二组中的指标值。因此，研究区农村地表水总体质量保持良好，但也有部分河流被氨氮和石油污染。因此，建立水质安全和风险评估体系以确保生产和生活用水十分必要。

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