DocumentCode
1647791
Title
Notice of Retraction
Food safety risk analysis based on generalized fuzzy numbers
Author
Jianling Xu ; Yong Deng
Author_Institution
Grain Econ. Inst., Nanjing Univ. of Finance & Econ., Nanjing, China
Volume
3
fYear
2010
Firstpage
699
Lastpage
702
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Generalized fuzzy numbers can deal with uncertain information in a more flexible manner than that of normal fuzzy numbers. In this paper, a food safety risk analysis model based on generalized fuzzy number,is proposed. First, a modified similarity measure is proposed. Then, the food safety risk analysis model is presented step by step. The modified operation rules on generalized fuzzy numbers have been presented. Finally, a risk analysis numerical example on food safety is used to show the efficiency of the proposed method.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Generalized fuzzy numbers can deal with uncertain information in a more flexible manner than that of normal fuzzy numbers. In this paper, a food safety risk analysis model based on generalized fuzzy number,is proposed. First, a modified similarity measure is proposed. Then, the food safety risk analysis model is presented step by step. The modified operation rules on generalized fuzzy numbers have been presented. Finally, a risk analysis numerical example on food safety is used to show the efficiency of the proposed method.
Keywords
food safety; fuzzy set theory; numerical analysis; risk management; food safety risk analysis; generalized fuzzy number; modified operation rules; risk analysis numerical example; Artificial intelligence; Biological system modeling; Economics; Facsimile; Fuzzy logic; Medical services; Generalized fuzzy numbers; risk analysis; similarity measures;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Management Science (ICAMS), 2010 IEEE International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4244-6931-4
Type
conf
DOI
10.1109/ICAMS.2010.5552869
Filename
5552869
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