基于主成分分析的地下水水质模糊综合评价

Fuzzy Comprehensive Evaluation of Groundwater Quality Based on Principal Component Analysis

主成分分析法能够降低数据维度,减少分析指标数量。利用主成分分析法分析初选指标,筛选模糊综合评价因子,求取其权重集,建立基于主成分分析的水质模糊综合评价模型,并应用于黄土地区洛河油田浅层地下水的水质评价中。结果表明,采用主成分分析法选择评价因子,既保证了评价结果的可靠性,又减小了参与评价的数据量,提高了评价效率;利用主成分分析法赋权进行模糊综合评价,考虑了评价因子之间的相互作用,水质评价结果比采用超标法赋权的结果更优;洛河油田富县区块浅层地下水水质状况总体较好,在油田开发过程中应采取保护措施,防止浅层地下水污染。

Principal component analysis（PCA）method can reduce the data dimension and the number of analysis index.The principal component analysis method is used to analyze the primary indexes,and the fuzzy comprehensive evaluation factors are selected.Then the weight set are got.Thus,a water quality fuzzy comprehensive evaluation model based PCA is established to evaluate water quality of shallow groundwater in an oil field in the loess area.The results show that the choice of evaluation factors based PCA not only ensures the reliability of the evaluation results,but also reduces the amount of data involved in the evaluation,and improves the evaluation efficiency.Fuzzy comprehensive evaluation based PCA weighting considers the interaction among the evaluation factors,which makes the water quality evaluation results better than that of over-standard weighting method.Quality status of shallow groundwater in Luohe oil field of Fuxian Country is generally good.But the measures should be taken in the process of oilfield development to prevent groundwater pollution.