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Notice of Retraction
New algorithm based on the BP neural network

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7 Author(s)
Zi-sheng Zhang ; Electrostatic Res. Inst., Hebei Univ., Baoding, China ; Ji-guang Wang ; Zhen-ya Yang ; Zhen-lei Xiao
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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.

In allusion to the defects of the slow convergence speed and the local minimum for traditional BP algorithm, a new algorithm is proposed. The new algorithm is designed by hierarchical genetic algorithm together with the algorithm of automatically adjusting the S form function, which combines with the BP network to improve the efficiency of fault detection. With calculation and simulation, compared with the traditional BP algorithm, the new algorithm has high precision of training, low training times, and small relative mean square error, which achieves better optimization results.

Published in:

Industrial and Information Systems (IIS), 2010 2nd International Conference on  (Volume:2 )

Date of Conference:

10-11 July 2010