改进灰色聚类关联分析法的综合评价及应用
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摘要
为权衡关联度值对等级排序的影响,采用点图分类排序方法对站点进行分类并对其空气质量排序进行优化调整。并对其和传统改进灰色聚类评价结果进行了对比分析。结果表明:株洲市城区空气质量综合评价等级总体处于Ⅱ级。应用基于不同归属等级的关联度值构成的向量来建立点图分类排序方法,对相邻站点进行优化调整,得到的排序更合理,符合实际情况。计算比较株洲市7个空气质量监测点季节及年度的污染状况,发现改进灰色聚类关联分析法对污染等级的敏感度更高,聚类评价结果更合理。表明改进灰色聚类关联分析法应用于大气环境质量评价具有重要实际价值。
To weigh the impact of correlation degree values on rank ordering, the point map classification method was used to classify the monitoring sites and optimize the air quality order. Finally, the traditional improved grey clustering analysis methods and the comprehensive evaluation level of air quality in Zhuzhou City is in Grade Ⅱ. The improved gray clustering relation analysis method were compared and analyzed. The results show that the point map classification method is established by using the vectors of correlation degree values based on different attribution levels. The optimal adjustment of adjacent stations are made, and the sorting is more reasonable and realistic. And the seasonal and annual pollution status of seven air quality monitoring stations in Zhuzhou City are calculated and compared, it is found that the improved gray clustering correlation analysis method was more sensitive to pollution level. The improved gray clustering correlation analysis have important practical value in atmospheric environment quality evaluation.
To weigh the impact of correlation degree values on rank ordering, the point map classification method was used to classify the monitoring sites and optimize the air quality order. Finally, the traditional improved grey clustering analysis methods and the comprehensive evaluation level of air quality in Zhuzhou City is in Grade Ⅱ. The improved gray clustering relation analysis method were compared and analyzed. The results show that the point map classification method is established by using the vectors of correlation degree values based on different attribution levels. The optimal adjustment of adjacent stations are made, and the sorting is more reasonable and realistic. And the seasonal and annual pollution status of seven air quality monitoring stations in Zhuzhou City are calculated and compared, it is found that the improved gray clustering correlation analysis method was more sensitive to pollution level. The improved gray clustering correlation analysis have important practical value in atmospheric environment quality evaluation.
引文
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[2]何再超,郑钦玉,卢坤,等.重庆市大气环境质量的模糊数学综合评价[J].西南农业大学学报,2005,27(3):397-400.
[3]徐卫国,张清宇,郭慧,等.灰色聚类修正模型在系统总量控制中的应用[J].中国环境科学,2006,(5):546-549.
[4]魏云鹤,王镇,郭晓玉.灰色关联度模型及其在大气环境质量评价中的应用[J].山东大学学报(工学版),2004,34(2):122-124.
[5]李恺.层次分析法在生态环境综合评价中的应用[J].环境科学与技术,2009,32(2):183-185.
[6]刘杰,杨鹏,吕文生,等.城市空气质量的BP和RBF人工神经网络建模及分类评价[J].安全与环境工程,2014,21(6):129-134+139.
[7]刘杰,杨鹏,吕文生,等.基于北京市6类污染物的环境空气质量评价方法[J].安全与环境学报,2015,15(1):310-315.
[8]胡军,许丽忠,张江山.基于改进灰色聚类法的大气环境质量综合评价[J].福建师范大学学报(自然科学版),2012,28(1):49-54.
[9]麻冰涓.基于改进的灰色聚类法的大气环境质量评价方法研究[D].郑州:郑州大学,2007.
[10]马艳琴,杨红艳,潘平奇.灰色聚类关联分析法的改进及其应用[J].数学的实践与认识,2013,43(19):166-172.
[11]未碧贵,常青,闫彩云.基于改进灰色聚类关联分析法的城市大气环境质量评价[J].兰州交通大学学报,2010,29(3):135-138.
[12]梁爱萍,侯祺棕,刘爱东.大气环境质量灰色聚类关联分析法的应用研究[J].工业安全与环保,2005,31(6):35-37.