DocumentCode
3297632
Title
Notice of Retraction
Optimal model and non-linear rectification method based on annealing-inspired genetic algorithm in sensors
Author
Wang Jianfang
Author_Institution
Coll. of Comput. & Inf. Technol., Nanyang Normal Univ., Nanyang, China
fYear
2010
fDate
25-27 June 2010
Firstpage
553
Lastpage
556
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 order to solve the problems on the non-linearity rectification of sensor systems, this paper combines with the advantages of genetic algorithm and simulated annealing, brings forward a non-linearity rectification method based on annealing-inspired genetic algorithm. The results of experiment show that not only the method can correct the nonlinearity,but also the precision after correcting is better than least square 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.
In order to solve the problems on the non-linearity rectification of sensor systems, this paper combines with the advantages of genetic algorithm and simulated annealing, brings forward a non-linearity rectification method based on annealing-inspired genetic algorithm. The results of experiment show that not only the method can correct the nonlinearity,but also the precision after correcting is better than least square method.
Keywords
genetic algorithms; nonlinear control systems; sensors; simulated annealing; annealing-inspired genetic algorithm; least square method; nonlinear rectification method; optimal model; sensor systems; simulated annealing; Chemical sensors; Educational technology; Equations; Genetic algorithms; Intelligent sensors; Least squares methods; Neural networks; Sensor phenomena and characterization; Sensor systems; Simulated annealing; annealing-inspired genetic algorithm; genetic algorithm; least square algorithm; non-linearity rectification; sensor;
fLanguage
English
Publisher
ieee
Conference_Titel
Educational and Network Technology (ICENT), 2010 International Conference on
Conference_Location
Qinhuangdao
Print_ISBN
978-1-4244-7660-2
Type
conf
DOI
10.1109/ICENT.2010.5532099
Filename
5532099
Link To Document