Application of entropy-weight based fuzzy matter-element model in evaluation of paddy field water-saving irrigation technology

Author(s):  
Yongxia Wei ◽  
Mingyang Qu ◽  
Zhongxue Zhang
2013 ◽  
Vol 477-478 ◽  
pp. 870-873
Author(s):  
Du Wu ◽  
De Shan Tang ◽  
Xing Wang Lu ◽  
Wen Zhong Yu

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 basically consistent. So entropy weight of attribute recognition model is applicable to the evaluation of the reservoir eutrophication and it can ensure the fairness and reasonableness of weight distribution.


2010 ◽  
Vol 439-440 ◽  
pp. 104-108
Author(s):  
Xi Ping Wang ◽  
Li Ying Yan

An entropy fuzzy matter-element model is combined, based on the establishment of credit risk evaluation index system of the power listed companies. The model uses entropy weight method to determine the weight of evaluation index, which has strong objectivity. The calculation results show that this model is scientific and practical.


Author(s):  
Tian Tao ◽  
Zhang Tiantian ◽  
Li Xiaoning ◽  
Tong Dajian

A TOPSIS evaluation index system of entropy weight of enterprise internal control quality based on fuzzy matter-element model was established to master the enterprise internal control quality comprehensively and analyze its influences on enterprise innovation performance accurately. Firstly, a composite fuzzy matter-element model was established based on the fuzzy matter-element theory. Secondly, weights of evaluation indexes were determined by the entropy weight method. Thirdly, the concept of relative closeness was developed by comparison with positive and negative ideal indexes. Finally, the internal control quality levels of 781 listed companies in Chin were measured by TOPSIS method. Results show that: weights of five level-1 indexes for enterprise internal control quality evaluation are different. Specifically, weights of Law & Regulation, Operation and Strategy are higher than those of Financial Statements and Assets Safety. In the level-2 index system, weights of “major litigation and arbitration cases”, “turnover of total assets” and “Tobin’s Q” occupy 66% of total weights. Listed companies which occupy the top10 position in term of internal control quality mainly belong to industries requiring strict monitoring and control over safety production. Enterprise internal control quality differs significantly among different industries. Research conclusions can provide methods and practical references to evaluate internal control quality of Chinese enterprises.


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