Title :
Notice of Retraction
An improved BP algorithm and application in the fault diagnosis of the diesel engine fuel system
Author_Institution :
Coll. of Inf. Eng., Jinhua Polytech., Jinhua, 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.
Back-Propagation algorithm is one of the most popular algorithms in neural network. But it converges slowly, easily falling into local minima. This paper presents an improved BP algorithm, which can adjust learning rate using golden section method. Based on the algorithm, a diesel engine fault diagnosis system is designed. The simulation results indicate that the algorithm has much faster learning speed and more superior learning precision compared with the standard BP algorithm.
Keywords :
backpropagation; diesel engines; fault diagnosis; fuel systems; mechanical engineering computing; neural nets; back-propagation algorithm; diesel engine fault diagnosis system; diesel engine fuel system; golden section method; improved BP algorithm; learning precision; learning rate; learning speed; neural network; standard BP algorithm; Algorithm design and analysis; Convergence; Diesel engines; Fault diagnosis; Fuels; Neurons; Training; BP algorithm; fault diagnosis; golden section; variable step-length;
Conference_Titel :
Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), 2011 2nd International Conference on
Conference_Location :
Dengleng
Print_ISBN :
978-1-4577-0535-9
DOI :
10.1109/AIMSEC.2011.6011266
