An Yan, Zou Zhihong, Li Ranran
School of Economics and Management, Beihang University, Beijing 100191, China.
Int J Environ Res Public Health. 2014 Mar 26;11(4):3507-20. doi: 10.3390/ijerph110403507.
A large number of parameters are acquired during practical water quality monitoring. If all the parameters are used in water quality assessment, the computational complexity will definitely increase. In order to reduce the input space dimensions, a fuzzy rough set was introduced to perform attribute reduction. Then, an attribute recognition theoretical model and entropy method were combined to assess water quality in the Harbin reach of the Songhuajiang River in China. A dataset consisting of ten parameters was collected from January to October in 2012. Fuzzy rough set was applied to reduce the ten parameters to four parameters: BOD5, NH3-N, TP, and F. coli (Reduct A). Considering that DO is a usual parameter in water quality assessment, another reduct, including DO, BOD5, NH3-N, TP, TN, F, and F. coli (Reduct B), was obtained. The assessment results of Reduct B show a good consistency with those of Reduct A, and this means that DO is not always necessary to assess water quality. The results with attribute reduction are not exactly the same as those without attribute reduction, which can be attributed to the α value decided by subjective experience. The assessment results gained by the fuzzy rough set obviously reduce computational complexity, and are acceptable and reliable. The model proposed in this paper enhances the water quality assessment system.
在实际水质监测过程中会获取大量参数。如果在水质评估中使用所有参数，计算复杂度肯定会增加。为了降低输入空间维度，引入模糊粗糙集进行属性约简。然后，将属性识别理论模型与熵权法相结合，对中国松花江哈尔滨段的水质进行评估。于2012年1月至10月收集了一个包含十个参数的数据集。应用模糊粗糙集将这十个参数约简为四个参数：五日生化需氧量（BOD5）、氨氮（NH3-N）、总磷（TP）和大肠杆菌（F. coli）（约简集A）。考虑到溶解氧（DO）是水质评估中的常用参数，还得到了另一个约简集，包括溶解氧、五日生化需氧量、氨氮、总磷、总氮（TN）、粪大肠菌群（F. coli）（约简集B）。约简集B的评估结果与约简集A的评估结果具有良好的一致性，这意味着评估水质时溶解氧并非总是必需的。属性约简后的结果与未进行属性约简的结果并不完全相同，这可能归因于由主观经验确定的α值。通过模糊粗糙集得到的评估结果明显降低了计算复杂度，并且是可接受且可靠的。本文提出的模型增强了水质评估系统。
