水质评价中模糊-集对分析法的改进

针对水环境的不确定性和模糊性,基于集对分析法和模糊理论相结合的评价模型已被广泛运用到水质评价当中。传统的评价模型在确定水质等级的复合算法中虽引入了权值的概念,但仍会出现指标浓度重复计算、信息丢失和指标权值的影响得不到体现等缺陷,具有局限性。针对这些缺陷,将基于加权后的内梅罗指数法思想应用于传统模糊-集对分析法中的复合算法上,考虑到加权内梅罗指数法兼顾极值的特性及计权性,通过取平均值和极值替代累加的方法来实现减小指标浓度重复计算的影响,同时加强复合算法中权值所占比重使得权值的作用得到充分体现。实验表明,改进的复合算法使得评价结果更为精确、客观。

An improved fuzzy-set pair analysis in water quality evaluation

In view of the uncertainty and ambiguity of water environment, the evaluation model based on set pair analysis theory and fuzzy theory has been widely applied in the water quality evaluation. Although the traditional evaluation model introduced the concept of weights, there still exist some defects in the compound algorithm which determines the level of water quality such as repeated calculation of the index concentration, loss of information, the impacts of the index weights neglected and so on. To overcome these shortcomings, Nemerow index method with weights is used on the compound algorithm of traditional Fuzzy-Set pair analysis. Taking into account the characteristics of extremes and weights of Nemerow index method, the impacts of repeated calculation of the index concentration can be reduced by taking average and extremum instead of accumulation, and the weight proportion of complex algorithms can be strengthened to sufficiently embody the use of the weights. Experiments show that the improved compound algorithm makes the evaluation more accurate and objective.