DocumentCode
3274423
Title
Notice of Retraction
The improvement of MPO and LS-SVM algorithm in soft measurement model of NIS
Author
Cao Shuanggui
Author_Institution
Dept. of Electr. Eng., Huaihai Inst. of Technol., Lianyungang, China
fYear
2011
fDate
15-17 April 2011
Firstpage
3699
Lastpage
3702
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.
Aiming at the shortage of accuracy and authenticity on data corrections in soft measurement Near Infrared Spectrometer, in order to overcome the traditional\´s disadvantages of "over-fitting" and "owe-fitting" at modelling and predicting, improved the algorithm of MPO and LS-SVM separately in the paper, adopt a complex correction algorithm based on MPSO and VWLS-SVM.when Near Infrared Spectrometer multiple correction model is built, MPSO algorithm is adopted to search the optimal sample weight. In the other, VWLS-SVM algorithm can using more wavelength variables. Finally, the model is built.The analysis shows that the algorithm has a good astringency and ergodicity. In the other, the algorithm is helpful to keep multichannel advantage and stability, and to obtain more precise and truly correction model.
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.
Aiming at the shortage of accuracy and authenticity on data corrections in soft measurement Near Infrared Spectrometer, in order to overcome the traditional\´s disadvantages of "over-fitting" and "owe-fitting" at modelling and predicting, improved the algorithm of MPO and LS-SVM separately in the paper, adopt a complex correction algorithm based on MPSO and VWLS-SVM.when Near Infrared Spectrometer multiple correction model is built, MPSO algorithm is adopted to search the optimal sample weight. In the other, VWLS-SVM algorithm can using more wavelength variables. Finally, the model is built.The analysis shows that the algorithm has a good astringency and ergodicity. In the other, the algorithm is helpful to keep multichannel advantage and stability, and to obtain more precise and truly correction model.
Keywords
infrared spectrometers; least squares approximations; particle swarm optimisation; security of data; support vector machines; MPSO algorithm; NIS; VWLS-SVM algorithm; complex correction algorithm; data correction authenticity; multiple particle swarm optimization; near infrared spectrometer multiple correction model; over-fitting; soft measurement model; variable-weighted least squares-support vector machines; Algorithm design and analysis; Classification algorithms; Hybrid power systems; Particle swarm optimization; Prediction algorithms; Predictive models; Support vector machines; Multiple Particle Swam Optimization; Near Infrared Spectrometer; Variable-Weighted Least Squares-Support Vector Machines; data classification;
fLanguage
English
Publisher
ieee
Conference_Titel
Electric Information and Control Engineering (ICEICE), 2011 International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-8036-4
Type
conf
DOI
10.1109/ICEICE.2011.5777317
Filename
5777317
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