DocumentCode
525903
Title
Notice of Retraction
Stability analysis of penstock based on IEP_ANN algorithm
Author
Dong Wensheng ; Guo Libing
Author_Institution
Inst. of Yellow River Sci., North China Inst. of Water Conservancy & Hydroelectric Power, Zhengzhou, China
Volume
2
fYear
2010
fDate
12-13 June 2010
Firstpage
57
Lastpage
61
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.
Stabilization problem of hydropower station penstock under external pressure is one of main control conditions of penstock design. At present, because of factors of assumption conditions and boundary simplification, the various calculation methods of the problem have their limitations; sometimes even calculation results have great differences. In this paper, penstock critical external pressure is simulated by artificial neural network model of based on immune evolutionary programming (IEP_ANN). The method better overcome easy premature convergence shortcoming of other evolutionary computations when solution group distribution is uneven. Example results show that method is feasible and its validity is verified. This paper provides an efficient solving path for stability problem of stiffening penstock under external pressure.
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.
Stabilization problem of hydropower station penstock under external pressure is one of main control conditions of penstock design. At present, because of factors of assumption conditions and boundary simplification, the various calculation methods of the problem have their limitations; sometimes even calculation results have great differences. In this paper, penstock critical external pressure is simulated by artificial neural network model of based on immune evolutionary programming (IEP_ANN). The method better overcome easy premature convergence shortcoming of other evolutionary computations when solution group distribution is uneven. Example results show that method is feasible and its validity is verified. This paper provides an efficient solving path for stability problem of stiffening penstock under external pressure.
Keywords
convergence; evolutionary computation; hydroelectric power stations; mechanical stability; neural nets; pressure control; stability; structural engineering; IEP-ANN algorithm; artificial neural network model; external pressure; hydropower station penstock; immune evolutionary programming; premature convergence; stability analysis; Biological system modeling; Hydroelectric power generation; Immune system; Neurons; Variable speed drives; artificial neural network; immunized evolutionary programming; penstock; structural stability component;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer and Communication Technologies in Agriculture Engineering (CCTAE), 2010 International Conference On
Conference_Location
Chengdu
Print_ISBN
978-1-4244-6944-4
Type
conf
DOI
10.1109/CCTAE.2010.5543998
Filename
5543998
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