• DocumentCode
    1597477
  • Title

    Notice of Violation of IEEE Publication Principles
    A New Optimization Algorithm for Dynamic Compensation of Sensors

  • Author

    Tian, WenJie ; Liu, JiCheng

  • Author_Institution
    Autom. Inst., Beijing Union Univ., Beijing, China
  • Volume
    2
  • fYear
    2010
  • Firstpage
    38
  • Lastpage
    41
  • Abstract
    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.
  • Keywords
    compensation; computerised instrumentation; identification; optimisation; stability; support vector machines; thermometers; artificial fish swarm algorithm; dynamic error correction; dynamic sensors compensation; identification; infrared thermometer; optimization algorithm; support vector machine; Frequency; Heuristic algorithms; Infrared sensors; Nonlinear dynamical systems; Sensor phenomena and characterization; Support vector machines; Temperature measurement; Temperature sensors; Thermal conductivity; Thermal resistance; AFSA; SVM model; compensation; identification; infrared thermomete;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Modeling and Simulation, 2010. ICCMS '10. Second International Conference on
  • Conference_Location
    Sanya, Hainan
  • Print_ISBN
    978-1-4244-5642-0
  • Electronic_ISBN
    978-1-4244-5643-7
  • Type

    conf

  • DOI
    10.1109/ICCMS.2010.223
  • Filename
    5421306