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首页> 美国卫生研究院文献>International Journal of Environmental Research and Public Health >Dynamic Assessment of Water Quality Based on a Variable Fuzzy Pattern Recognition Model
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Dynamic Assessment of Water Quality Based on a Variable Fuzzy Pattern Recognition Model

机译：基于可变模糊模式识别模型的水质动态评价

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摘要

Water quality assessment is an important foundation of water resource protection and is affected by many indicators. The dynamic and fuzzy changes of water quality lead to problems for proper assessment. This paper explores a method which is in accordance with the water quality changes. The proposed method is based on the variable fuzzy pattern recognition (VFPR) model and combines the analytic hierarchy process (AHP) model with the entropy weight (EW) method. The proposed method was applied to dynamically assess the water quality of Biliuhe Reservoir (Dailan, China). The results show that the water quality level is between levels 2 and 3 and worse in August or September, caused by the increasing water temperature and rainfall. Weights and methods are compared and random errors of the values of indicators are analyzed. It is concluded that the proposed method has advantages of dynamism, fuzzification and stability by considering the interval influence of multiple indicators and using the average level characteristic values of four models as results.
机译：水质评估是水资源保护的重要基础，并受到许多指标的影响。水质的动态和模糊变化导致需要适当评估的问题。本文探索了一种根据水质变化的方法。该方法基于可变模糊模式识别（VFPR）模型，并将层次分析模型（AHP）与熵权（EW）方法相结合。该方法被用于动态评估碧流河水库（中国达兰）的水质。结果表明，由于水温和降雨增加，水质水平在2到3之间，在8月或9月更差。比较权重和方法，分析指标值的随机误差。通过考虑多个指标的区间影响，并以四个模型的平均水平特征值作为结果，得出该方法具有动态性，模糊性和稳定性的优点。

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