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Eutrophication Assessment Based on the Cloud Matter Element Model

机译：基于云物元模型的富营养化评估

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摘要

Eutrophication has become one of the most serious problems threatening the lakes/reservoirs in China over 50 years. Evaluation of eutrophication is a multi-criteria decision-making process with uncertainties. In this study, a cloud matter element (CME) model was developed in order to evaluate eutrophication level objectively and scientifically, which incorporated the randomness and fuzziness of eutrophication evaluation process. The elements belonging to each eutrophication level in the CME model were determined by means of certainty degrees through repeated simulations of cloud model with reasonable parameters of expectation , entropy , and hyper-entropy . The weights of evaluation indicators were decided by a combination of entropy technology and analytic hierarchy process method. The neartudes of water samples to each eutrophication level of lakes/reservoirs in the CME model were generated and the eutrophication levels were determined by maximum neartude principal. The proposed CME model was applied to evaluate eutrophication levels of 24 typical lakes/reservoirs in China. The results of the CME model were compared with those of comprehensive index method, matter element model, fuzzy matter element model, and cloud model. Most of the results obtained by the CME model were consistent with the results obtained by other methods, which proved the CME model is an effective tool to evaluate eutrophication.
机译：富营养化已经成为50年来威胁中国湖泊/水库的最严重问题之一。富营养化的评估是一个具有不确定性的多标准决策过程。为了客观，科学地评价富营养化水平，建立了云物质元素（CME）模型，该模型结合了富营养化评价过程的随机性和模糊性。通过对云模型的重复模拟，以合理的期望值，熵和超熵参数，通过确定度确定CME模型中每个富营养化水平的元素。评价指标的权重由熵技术和层次分析法相结合确定。生成了CME模型中每个湖泊/水库富营养化水平的水样近邻，并通过最大近邻原理确定了富营养化水平。提出的CME模型被用于评估中国24个典型湖泊/水库的富营养化水平。将CME模型的结果与综合指标法，物元模型，模糊物元模型和云模型的结果进行了比较。 CME模型获得的大多数结果与其他方法获得的结果一致，证明CME模型是评估富营养化的有效工具。

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