DocumentCode
2234544
Title
Notice of Violation of IEEE Publication Principles
Dynamic Compensation for Infrared Thermometer Based on SVR and Immune Clone Selection Algorithm
Author
Tian, WenJie ; Ai, Lan ; Geng, Yu ; Jicheng Liu
Author_Institution
Autom. Inst., BEIJING Union Univ., Beijing, China
fYear
2009
fDate
24-25 April 2009
Firstpage
61
Lastpage
65
Abstract
Notice of Violation of IEEE Publication Principles
"Dynamic Compensation for Infrared Thermometer Based on SVR and Immune Clone Selection Algorithm"
by WenJie Tian, Yu Geng, Lan Ai, JiCheng Lu
in the International Conference on Industrial and Information Systems, 2009, pp. 61–65
After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE\´s Publication Principles.
This paper contains significant portions of original text from the paper cited below. The original text was copied with insufficient attribution (including appropriate references to the original author(s) and/or paper title) and without permission.
Due to the nature of this violation, reasonable effort should be made to remove all past references to this paper, and future references should be made to the following article:
"Infrared thermometer sensor dynamic error compensation using Hammerstein neural network"
by Dehui Wu, Songling Huang, Wei Zhao, Junjun Xin
in Sensors and Actuators A: Physical, 2009, Pages 152 – 158
A novel structure of dynamic model is proposed in this paper and applied to construct a dynamic model to correct the dynamic errors of the infrared thermometer, because of which the dynamic performance of the thermometer is effectively improved. The dynamic compensator is established and the compensation is described and explicated by the support vector machine (SVM) model. According to SVM model, the novel structure is devised. The identification of thermometer non-linear dynamic compensator is achieved by immune clone selection algorithm. The results show that the stabilizing time of the thermometer is reduced less than 7 ms from 26 ms and the dynamic performance is obviously improved after compensation.
"Dynamic Compensation for Infrared Thermometer Based on SVR and Immune Clone Selection Algorithm"
by WenJie Tian, Yu Geng, Lan Ai, JiCheng Lu
in the International Conference on Industrial and Information Systems, 2009, pp. 61–65
After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE\´s Publication Principles.
This paper contains significant portions of original text from the paper cited below. The original text was copied with insufficient attribution (including appropriate references to the original author(s) and/or paper title) and without permission.
Due to the nature of this violation, reasonable effort should be made to remove all past references to this paper, and future references should be made to the following article:
"Infrared thermometer sensor dynamic error compensation using Hammerstein neural network"
by Dehui Wu, Songling Huang, Wei Zhao, Junjun Xin
in Sensors and Actuators A: Physical, 2009, Pages 152 – 158
A novel structure of dynamic model is proposed in this paper and applied to construct a dynamic model to correct the dynamic errors of the infrared thermometer, because of which the dynamic performance of the thermometer is effectively improved. The dynamic compensator is established and the compensation is described and explicated by the support vector machine (SVM) model. According to SVM model, the novel structure is devised. The identification of thermometer non-linear dynamic compensator is achieved by immune clone selection algorithm. The results show that the stabilizing time of the thermometer is reduced less than 7 ms from 26 ms and the dynamic performance is obviously improved after compensation.
Keywords
computerised instrumentation; genetic algorithms; support vector machines; temperature measurement; thermometers; dynamic errors correct; immune clone selection algorithm; infrared thermometer; support vector machine; thermometer nonlinear dynamic compensator; Automation; Cloning; Frequency; Sensor phenomena and characterization; Support vector machines; Temperature distribution; Temperature measurement; Temperature sensors; Thermal conductivity; Thermal resistance; SVM model; compensation; identification; immune clone selection algorithm; infrared thermometer;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial and Information Systems, 2009. IIS '09. International Conference on
Conference_Location
Haikou
Print_ISBN
978-0-7695-3618-7
Type
conf
DOI
10.1109/IIS.2009.30
Filename
5116296
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