摘要
为了解决普遍意义上的水质模糊识别理论不能评价指标数据超过5级标准值和最大隶属度原则的缺点,本文提出6级水质计算方法来改进模糊模式识别模型。再者,引入Set Pair Analysis(SPA)理论处理等级标准间的不确定性信息。从而构建引入SPA的6级模糊模式识别模型,将其运用于河流实例中。评价结果表明:引入SPA的6级模糊模式识别模型更能准确地确定水质综合等级,为治理河流水质污染提供理论支持。
In order to solve the general evaluation shortcomings of the fuzzy recognition theory on 5 level standard values and the maximum membership degree principle, this study puts forward the calculation method of 6 level water quality to improve the model of fuzzy pattern recognition, furthermore, the Pair Analysis Set （SPA） theory was introduced to deal with the uncertainty information between the different standard levels, then the fuzzy pattern recognition model was established to be applied in river systems. The evaluation results showed that the 6 level fuzzy pattern recognition model based on SPA was more accurate to determine the water quality comprehensive grade, which could provide theoretical support for the treatment of river water pollution.
出处
《水资源与水工程学报》
2016年第6期1-6,共6页
Journal of Water Resources and Water Engineering
基金
国家重点基础研究发展计划(973计划)(2012CB417006)
"十一五"国家科技支撑计划(2009BAC56B03)
关键词
模糊模式识别模型
集对分析理论
6级相对最优隶属度
水质评价
fuzzy pattern recognition model
set pair analysis
6 -level relative optimal membership degree
water quality evaluation
