基于属性识别模型的湖泊富营养化评价  

Eutrophication assessment of lake based on attribute recognition model

作　　者：胡吉炜[1] 高军省[1,2] 

机构地区：[1]长江大学地球环境与水资源学院,湖北武汉430100 [2]华北水利水电学院,河南郑州450011

出　　处：《水资源与水工程学报》2013年第4期127-130,共4页Journal of Water Resources and Water Engineering

基　　金：国家水体污染控制与治理科技重大专项(2009ZX07210-006-3-2)

摘　　要：为合理地确定湖泊的富营养化状态,从属性识别理论出发,建立了湖泊富营养化评价的属性识别模型,并结合熵权法确定的权重系数对东昌湖的富营养化状态进行评价。评价结果为各湖区全年均属于富营养化级别,并且7月份的富营养化程度最高,12月份次之,4月份最低,这与集对分析法和模糊识别方法评价的结果一致。表明该模型的评价结果是合理的;同时该模型简便、易懂,可作为湖泊富营养化评价的一种可行方法。In order to determine the state of lake eutrophication, starting from the attribute recognition theory, the paper established the attribute recognition model for the eutrophication assessment of lake, and combined with the weight coefficients determined by entropy method to evaluate the state of eutrophi- cation of Dongchang lake. The result is that the lake district throughout the year belongs to eutrophication level, and the highest degree of eutrophication is July, followed by December, the lowest degre of that is April. This result is consistent with the result evaluated by set pair analysis and fuzzy recognition method. The evaluation result of the model is reasonable. The model is simple, easy to be understand and can be used as a feasible way for the eutrophication assessment of lake.

关 键 词：属性识别 富营养化 熵权 湖泊 

分 类 号：X824[环境科学与工程—环境工程]