摘要
提出基于投影寻踪函数和云模型的水质综合评价模型,选取太湖流域20个样本盐度、氯化物、氨氮、溶解性固体4类具有代表性的农业灌溉水质监测数据,在综合其投影值及隶属度基础上,计算农业灌溉水质的等级区分粒度。结果表明,投影寻踪模型计算值平均绝对误差仅为0.125 2级,达到了较好的水质评价精确度,同时利用云模型计算各个监测指标得到的最大综合确定度所属级别与经验等级一致。
This paper proposed a comprehensive evaluation model of water quality based on projection pursuit function and cloud model, 4 representative water quality monitoring data of agricultural irrigation water collected from 20 samples in Taihu River Basin were selected, covering salinity, chloride, ammonia nitrogen and dissolved solids. On the basis of synthesizing their projection value and membership degree, the grade discrimination granularity of the agricultural irrigation water quality was calculated, the results show that the average absolute error of the calculated value of the projection pursuit model was only 0. 1252, w h i c h m e a n s the accuracy of water quality evaluation has been achieved preferably. Meanwhile, the maximum comprehensive certainty degree of each monitoring index calculated by cloud model was consistent with the experience grade.
作者
于嘉骥
张慧妍
王小艺
许继平
王立
YU Jiaji;ZHANG Huiyan;WANG Xiaoyi;XU Jiping;WANG Li(School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China;Beijing Key Laboratory of Big Data Technology for Food Safety y Beijing Technology and Business University, Beijing 1 0 0 0 4 8 , China)
出处
《水资源保护》
CAS
CSCD
2017年第6期142-146,共5页
Water Resources Protection
基金
北京市属高校创新能力提升计划(PXM2014_014213_000033)
北京市教委科技计划重点项目(KZ201510011011)
关键词
水质评价
农业灌溉
投影寻踪
云模型
等级区分粒度
water quality evaluation
agricultural irrigation
projection pursuit
cloud m o d e l
grade distinguish granularity
