改进的模糊综合评价法及在给水厂原水水质评价中的应用

基于模糊评价原理,针对传统模糊评价模型存在的评价因子选取主观性强,评价结果可比性差及超标因子存在性表述不直观等问题,建立了基于主成分分析的模糊综合评价模型.利用主成分分析的降维原理筛选评价因子,降低主观因素对评价结果的影响,并以级别特征值J作为同级别水体水质优劣比较和超标因子存在性判定的依据,提高模型的实用性.最后应用该模型对西北某市地下水源水厂原水水质进行综合评价.结果表明,案例水厂原水合格率高于80％,且评价结果以Ⅰ类水为主,总体符合国家标准要求,但各年反映水体特征的主要影响因子有所差异.当级别特征值J大于2时,无论最终评价结果优劣,均表明评价水体存在超标因子,且J值越大,水体状况越差.以筛选后的水质指标作为评价因子,所得评判结果更贴近水体实际状况,所得J值能更准确地反映超标因子的存在,使得最终评价结果更加科学、合理.

Improved fuzzy synthetic evaluation method and its application in raw water quality evaluation of water supply plant

Based on the traditional fuzzy synthetic evaluation theory, a new model based on principal component analysis is proposed to overcome the limitations of traditional model in practice, such as factor selection and results analysis. In the new model, factors were selected by dimension reduction principle. The difference of quality level and existence of over-proof factors were characterized by level characteristic value (J). Meanwhile, a case study of source water quality assessment, using the improved model in a city of northwest China, was presented. The result showed that over 80% of the water samples accorded with the national quality standard of potable water, with mostly in class I. However, the main factors for water quality standards differed over the years. When the level characteristic value (J) was greater than two, over-proof factors existed regardless of the assessment result. The greater the level characteristic value was, the worse the water quality. When the screened indices were taken as the assessment factors, the level characteristic value could reflect the existence of over-proof factors more accurately.