摘要
主成分分析法可以在损失很少原始信息的前提下将影响地表水质的多个因子简化为几个综合因子,但无法对综合水质情况进行描述;模糊综合评价法可以描述出地表水质的综合评价等级,但评价因子多为人为选取,存在较强的主观性。鉴于此,以嘉陵江水质现状评价为例,利用主成分分析法选取影响各断面水质的关键因子,将其作为模糊综合评价的评价因子,建立了模糊-主成分分析综合评价法的地表水水质耦合评价模型。研究结果表明,该模型能很好地体现分析因子对评价结果带来的影响,使得评价结果更科学、合理。
Principal components analysis,based on which,data dimensions can be effectively reduced while keeping original information,which will reduce groundwater quality factors to a few more comprehensive factors. However,the expression of comprehensive water quality status of groundwater can't be made directly. Fuzzy comprehensive evaluation method can be obtained with synthetic water quality objective,but the evaluation factors are frequently selected too subjectively. In view of this,this paper takes the surfacewater quality evaluation of Liaoning SI mountain mining area as an example,using principal component analysis method to select the key factors affect the water quality section,which will be used as evaluation factors of fuzzy comprehensive evaluation,and establishes the coupling model of groundwater quality assessment based on principal component analysis- fuzzy comprehensive evaluation method. Research results show that the model can epitomize the impact of factor analysis on the evaluation results,making the results more scientific and rational.
出处
《水利科技与经济》
2016年第10期8-12,共5页
Water Conservancy Science and Technology and Economy
关键词
主成分
模糊综合
地表水
水质
principal component
fuzzy comprehensive
surfacewater
water quality
