基于改进的模糊物元模型的河流水质评价
Assessment of River Water Quality Based on an Improved Fuzzy Matter-Element Model.
机构信息
School of Energy and Environment, Southeast University, Nanjing 210096, China.
School of Glasgow, University of Electronic Science and Technology, Chengdu 610054, China.
出版信息
Int J Environ Res Public Health. 2019 Aug 5;16(15):2793. doi: 10.3390/ijerph16152793.
In this paper, an improved fuzzy matter-element (IFME) method was proposed, which integrates the classical matter-element (ME) method, set pair analysis (SPA), and variable coefficient method (VCM). The method was applied to evaluate water quality of five monitor stations along Caoqiao River in Yixing city, Jiangsu Province, China. The levels of river water quality were determined according to fuzzy closeness degree. Compared with the traditional evaluation methods, the IFME method has several characteristics as follows: (i) weights were determined by the VCM method, which can reduce workload and overcome the adverse effects of abnormal values, (ii) membership degrees were defined by SPA, which can utilize monitored data more scientifically and comprehensively, and (iii) IFME is more suitable for seriously polluted rivers. Overall, these findings reinforce the notion that an integrated approach is essential for attaining scientific and objective assessment of river water quality.
本文提出了一种改进的模糊物元（IFME）方法，该方法综合了经典物元（ME）方法、集对分析（SPA）和变权系数法（VCM）。该方法应用于评估中国江苏省宜兴市漕桥河五个监测站的水质。根据模糊贴近度确定河流水质水平。与传统评价方法相比，IFME 方法具有以下几个特点：（i）权重由 VCM 方法确定，可减少工作量并克服异常值的不利影响；（ii）隶属度由 SPA 定义，可更科学、更全面地利用监测数据；（iii）IFME 更适用于污染严重的河流。总的来说，这些发现强化了一个观点，即综合方法对于实现河流水质的科学和客观评估至关重要。
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