2013
DOI: 10.4028/www.scientific.net/amm.477-478.870
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The Application of Entropy Weight of Attribute Recognition Model in Reservoir Eutrophication Evaluation

Abstract: Subjective factors could affect the weight distribution of each index in evaluation of reservoir eutrophication, so the example used entropy to deal with the weight distribution of each index. Combined attributes recognition method, the writer selected six indicators to build the entropy weight of attribute recognition model about reservoir eutrophication of ten large reservoirs in Guangdong Province. By comparing the calculated results with the results of matter-element model, the calculation results were bas… Show more

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Cited by 4 publications
(2 citation statements)
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“…e entropy weight method was applied to the weight calculation to reduce the subjectivity brought by expert grading according to the G1 method. It could determine the weight of relevant factors by analyzing the amount of the information entropy of the respective indicator value [24,25]. e smaller the information entropy is, the greater the weight of the indicator would be.…”
Section: Entropy Weight Methodmentioning
confidence: 99%
“…e entropy weight method was applied to the weight calculation to reduce the subjectivity brought by expert grading according to the G1 method. It could determine the weight of relevant factors by analyzing the amount of the information entropy of the respective indicator value [24,25]. e smaller the information entropy is, the greater the weight of the indicator would be.…”
Section: Entropy Weight Methodmentioning
confidence: 99%
“…Since different indicators have differently important roles to play in supply chain development, calculating the weighting coefficients of various indicators is prerequisite [42]. This paper combines Stata with the Entropy Weight Method (EWM) to determine specific weighting coefficients, and the smaller the entropy, the greater the weighting coefficient of an indicator [43]. To make the panel data from 2008 to 2019 of 31 provinces more comparable, this paper further introduces the variable of time on the basis of two original variables, namely research objects and assessment indicators.…”
Section: Natural Environmentmentioning
confidence: 99%