文章摘要
胡吉炜,高军省.基于属性识别模型的湖泊富营养化评价Journal of Water Resources and Water Engineering[J].,2013,24(4):127-130
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
Received:January 12, 2013  Revised:March 14, 2013
DOI:10.11705/j.issn.1672-643X.2013.04.031
中文关键词: 属性识别  富营养化  熵权  湖泊
英文关键词: attribute recognition  eutrophication  entropy weight  lake
基金项目:国家水体污染控制与治理科技重大专项(2009ZX07210-006-3-2)
Author NameAffiliation
HU Jiwei College of Earth Environment and Water Resources, Yangtze University, Wuhan 430100, China 
GAO Junsheng College of Earth Environment and Water Resources, Yangtze University, Wuhan 430100, China 
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中文摘要:
      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。
英文摘要:
      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 eutrophication 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.
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