Application of Improved Set Pair Analysis Model for Evaluation of Lake Eutrophication

Li, Fanxiu

doi:10.1109/cdciem.2011.488

Cited by 2 publications

(2 citation statements)

References 7 publications

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“…In order to set up a five-element connection number in relation to I-V grades evaluation standard commonly used in lake assessment the b-discrepancy degree was expanded into -partial identity in discrepancy degree, -entirety discrepancy degree and -partial contrary in discrepancy degree [12]. This forms a multivariate connection number of a-identity degree, -partial identity in discrepancy degree, -entirety discrepancy degree, -partial contrary in discrepancy degree and c-contrary degree of set pair.…”

Section: 1set Pair Analysismentioning

confidence: 99%

Evaluation of lake eutrophication status based on set pair analysis and confidence intervals

Mulenga

2018

int.jour.sci.res.mana

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Because traditional assessing methods usually yield extreme results and are of poor resolution, a set pair analysis based on triangular fuzzy number is established. Set pair analysis method is an uncertainty analysis method of the system whose formula structure analysis of connection degree is established by the identity degree, discrepancy degree and contrary degree to deal with all kinds of uncertainty and fuzzy problems. The measured value and the lake quality criteria are two interrelated sets put together to compose a set pair with respect to the problem of determination of the magnitude of lake eutrophication. The basic expression of the degree of couplet is extended at different levels and at the same level to form a multi-element connection number, in order to set up a five-element connection number in relation to I-V grades evaluation standard commonly used in lake assessment. The discrepancy degree is expanded into partial identity in discrepancy, entirety discrepancy and partial contrary in discrepancy, this forms a multivariate connection number of identity, partial identity in discrepancy, entirety discrepancy, partial contrary in discrepancy and contrary. By introducing triangular fuzzy number the number of links to get the evaluation grade for a confidence interval was obtained, weight value calculated by weighted average method and finally got the evaluation grade as a confidence interval based on confidence level. The case study shows that the method presents the evaluating grade as a confidence interval which has advantages of high resolution and information utilization.

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Section: 1set Pair Analysismentioning

confidence: 99%

Evaluation of lake eutrophication status based on set pair analysis and confidence intervals

Mulenga

2018

int.jour.sci.res.mana

Self Cite

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“…Conventional evaluation methods like TLI cannot reflect the detailed characteristics of eutrophication. erefore, Lin et al [20] applied the principle of set pair analysis to assess the degree of lake eutrophication. Set pair analysis has been widely used to study the system with certainty and uncertainty [21].…”

Section: Introductionmentioning

confidence: 99%

Multidimensional Connection Cloud Model Coupled with Improved CRITIC Method for Evaluation of Eutrophic Water

Yan

Wang

et al. 2022

Mathematical Problems in Engineering

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The degree of eutrophication in the water environment is deepening. For the appropriate treatment of eutrophication, it is essential to evaluate it accurately. However, the evaluation of eutrophication has not been well solved because it is full of uncertainty. Herein, a multidimensional connection cloud model, combined with the improved CRITIC (Criteria Importance Through Inter-criteria Correlation) method, was put forward here to assess water eutrophication and depict the randomness, ambiguity, and interaction of evaluation factors. First, an improved CRITIC was adopted to determine indicator weight so that the correlation among different indicators and more information were depicted. Secondly, a multidimensional connection cloud was simulated to characterize fuzzy indicators and ambiguous classification boundary values according to classification criteria. Next, the connection degree was calculated relative to the evaluation standard. The eutrophication grade was specified under the “maximum connection degree” principle. At last, the effectiveness and practicality of the model proposed here were affirmed by two cases and comparisons with supplementary methods. The results suggest that the proposed model can avoid shortcomings of the original CRITIC method and cloud model, and make the assessment result more realistic.

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Application of Improved Set Pair Analysis Model for Evaluation of Lake Eutrophication

Cited by 2 publications

References 7 publications

Evaluation of lake eutrophication status based on set pair analysis and confidence intervals

Evaluation of lake eutrophication status based on set pair analysis and confidence intervals

Multidimensional Connection Cloud Model Coupled with Improved CRITIC Method for Evaluation of Eutrophic Water

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