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Notice of Violation of IEEE Publication Principles
"A New Optimization Algorithm for Dynamic Compensation of Sensors"
by WenJie Tian, JiCheng Liu
in 2010 Second International Conference on Computer Modeling and Simulation (ICCMS 2010), 2010, pp. 38 – 41.
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 and improved artificial fish swarm algorithm (AFSA) are 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 artificial fish swarm algorithm. The results show that the stabilizing time of the thermometer is reduced and the dynamic performance is obviously improved after compensation.