DocumentCode
475956
Title
Notice of Retraction
Fuzzy optimization model based on synthesizing effect and inequity degree
Author
Chen-Xia Jin ; Fa-Chao Li
Author_Institution
Sch. of Econ. & Manage., Hebei Univ. of Sci. & Technol., Shijiazhuang
Volume
1
fYear
2008
fDate
12-15 July 2008
Firstpage
517
Lastpage
522
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.
In this paper, based on the structure of fuzzy information and the mechanism of fuzzy optimization, we propose the concept of quasi-linear fuzzy number; by distinguishing principal index and secondary indices, we give the comparison method based on synthesizing effect combining with the compound qualification strategy of fuzzy information; starting from the essence of constraints, we give a fuzzy optimization model based on synthesizing effect and inequity degree (BID & SE-FOM), and propose an instructive fuzzy genetic algorithm based on principal operation and quasi-linear fuzzy numbers(PO QL-FGA); Finally, we analyze the performance of PO QL-FGA by using Markov chain theory, and further explain the application of quasi-linear fuzzy numbers by a concrete example.
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.
In this paper, based on the structure of fuzzy information and the mechanism of fuzzy optimization, we propose the concept of quasi-linear fuzzy number; by distinguishing principal index and secondary indices, we give the comparison method based on synthesizing effect combining with the compound qualification strategy of fuzzy information; starting from the essence of constraints, we give a fuzzy optimization model based on synthesizing effect and inequity degree (BID & SE-FOM), and propose an instructive fuzzy genetic algorithm based on principal operation and quasi-linear fuzzy numbers(PO QL-FGA); Finally, we analyze the performance of PO QL-FGA by using Markov chain theory, and further explain the application of quasi-linear fuzzy numbers by a concrete example.
Keywords
Markov processes; fuzzy set theory; genetic algorithms; Markov chain; compound qualification strategy; fuzzy information; fuzzy optimization model; instructive fuzzy genetic algorithm; quasilinear fuzzy numbers; Compounds; Convergence; Cybernetics; Genetic algorithms; Indexes; Machine learning; Optimization; BID&SE-FOM; Fuzzy optimization; Inequity degree; Quasi-linear fuzzy number; Synthesizing effect;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2008 International Conference on
Conference_Location
Kunming
Print_ISBN
978-1-4244-2095-7
Type
conf
DOI
10.1109/ICMLC.2008.4620459
Filename
4620459
Link To Document