Title :
Notice of Retraction
IVC fault diagnosis based on the improved BP neural network
Author :
Bo Qu ; Huijuan Gu
Author_Institution :
Sch. of Electron. & Inf. Eng., Soochow Univ., Suzhou, China
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.
The improved BP neural network is researched. It is the first time to present the method of IVC fault diagnosis based on the improved BP neural network.. First, the maulti-faults integral diagnostics model will be used to diagnose and then the single-fault parallel diagnosis model is introduced according to the fault characters of IVC. The result of the research shows that the later method is apparently better than the former with its higher validity.
Keywords :
backpropagation; fault diagnosis; laboratory techniques; neural nets; BP neural network; IVC fault diagnosis; Neurons; Artificial neural network; BP network; Fault diagnosis; IVC;
Conference_Titel :
Industrial and Information Systems (IIS), 2010 2nd International Conference on
Conference_Location :
Dalian
Print_ISBN :
978-1-4244-7860-6
DOI :
10.1109/INDUSIS.2010.5565699
