组合权重模糊联系度模型在水质评价中的应用

叶章蕊; 卢毅敏

doi:10.11988/ckyyb.20150615

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raybet体育在线院报 ›› 2016, Vol. 33 ›› Issue (9) : 33-39. DOI: 10.11988/ckyyb.20150615

水资源与环境

组合权重模糊联系度模型在水质评价中的应用

叶章蕊^a，b，卢毅敏^a，b

作者信息 +

Application of Fuzzy Connection Degree Model Based on Combined Weights to Evaluate Water Quality

YE Zhang-rui^1,2,LU Yi-min^1,2

Author information +

文章历史 +

摘要

针对水质评价指标存在的不确定性和水质评价标准存在的模糊性，基于集对分析理论与模糊层次分析法构建了模糊联系度水质评价模型。首先计算各评价指标值的分级联系度，对样本指标值做初步分类;再计算各评价样本与水质标准之间的综合联系度;最后通过置信度准则评判评价样本的水质级别。为突出不同评价指标的贡献率，将熵值赋权法和超标加权法引入该模型，并通过理想点法进行权重的合成，实现了多种赋权方法优势的融合。将模型应用于闽江渔业水域的水质评价，结果表明基于组合权重的模糊联系度水质评价结果更贴近实际情况，评价结果合理可信。

Abstract

In view of the uncertainty of evaluation indexes of water quality and the fuzziness of water quality standard, a fuzzy connection degree model of water quality evaluation was constructed based on set pair analysis and fuzzy analytical hierarchy process. First of all, the index values of water samples were preliminarily classified by calculating the hierarchical connection degree of each evaluation index value. Then the comprehensive degree of connection between samples and water quality standard was calculated. Finally, water quality grade was judged by confidence criterion. To highlight the contribution of different evaluation indexes, entropy method and super weighting method were introduced. Then the weights were combined based on ideal point method, by which the index weights were more reasonable. This model was applied to the evaluation of the fishery waters of Minjiang River, and the result was compared with those from gray classification method, synthesis index method and single factor evaluation method. The results obtained by the proposed model were closer to the real situation, and hence are reliable.

导出引用

叶章蕊，卢毅敏. 组合权重模糊联系度模型在水质评价中的应用[J]. raybet体育在线院报. 2016, 33(9): 33-39 https://doi.org/10.11988/ckyyb.20150615

YE Zhang-rui,LU Yi-min. Application of Fuzzy Connection Degree Model Based on Combined Weights to Evaluate Water Quality[J]. Journal of Changjiang River Scientific Research Institute. 2016, 33(9): 33-39 https://doi.org/10.11988/ckyyb.20150615

中图分类号： X824

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