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Notice of Retraction
Displacement Back-Analysis of rock-fill dam based on particle swarm optimization and genetic neural network algorithm

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4 Author(s)
Qiao Yan ; Coll. of Hydraulic & Environ. Eng., China Three Gorges Univ., Yichang, China ; ChangBin Wu ; Songzhao Lv ; MingLiang Bi

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 view of the complexity of Back Analysis of rock-fill material parameter, this paper uses genetic algorithm optimization BP neural network weights and threshold, simulated finite element calculation of rockfill dam by genetic neural network, combined with the theory of particle swarm optimization algorithm, and has realized inverse analysis of particle swarm optimization and genetic neural network. The results showed that: the simulation result coincides well with the experimental result, and inversion results could meet the computing requirements. This method can be widely used to solve various complicated engineering problems that target functions can't be expressed by apparent functions of decisive variables.

Published in:

Computer Application and System Modeling (ICCASM), 2010 International Conference on  (Volume:5 )

Date of Conference:

22-24 Oct. 2010