scholarly journals Eutrophication Assessment Based on the Cloud Matter Element Model

Author(s):  
Yumin Wang ◽  
Xian’e Zhang ◽  
Yifeng Wu

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 Ex, entropy En, and hyper-entropy He. 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.

Author(s):  
Xuesong Guo ◽  
Naim Kapucu

Abstract A Fuzzy Analytic Hierarchy Process based model was proposed and evaluated for social vulnerability assessment using a case study. The evaluation process is formulated as a multiple criteria decision making problem under uncertainty, where the subjective and imprecise judgements of multiple decision makers are represented as fuzzy numbers. Based on factors extracted from literature review, the researchers determined the factor weights and calculated social vulnerability scores for each county (district) using the Fuzzy Analytic Hierarchy Process method. The researchers demonstrated how the social vulnerability scores of counties (districts) and factor weights change under different uncertainties via sensitivity analysis. The results were comparted with data produced by conventional Analytic Hierarchy Process to test performance of the proposed method. The results show social vulnerability of each county (district) in Ankang City, implying the Urban-Rural Gap exist in current Chinese disaster management system. Most important sub-factors contributing to social vulnerability were also highlighted according to the results on factor weights.


2015 ◽  
Vol 713-715 ◽  
pp. 1610-1614
Author(s):  
Yan Li ◽  
Xiao Dong Mu ◽  
Wei Song ◽  
Hui Wei Shi

When using the traditional AHP to evaluate the system,the method of endow with weight is to request expert build the judgment matrix of every hierarchies. The method is over-subjective for its overdependence on expert system. In view of this, this paper puts forward an analytic hierarchy process method based on the cask theory. This method penalizes the index whose index value is too low to having a strong impact on overall system performance. Using this method achieves the goal of reducing the subjectivity. Finally, according to the example, this method’s superiority is proved.


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