›› 2011, Vol. 32 ›› Issue (2): 547-552.

• Geotechnical Engineering • Previous Articles     Next Articles

Study of interval parameters back analysis of dam body and rock foundation based on RNN model

LEI Peng 1－3, SU Huai-zhi4, ZHANG Gui-jin1   

  1. 1. School of Water Conservancy, Changsha University of Science and Technology, Changsha 410114, China; 2. Mid-south Design and Research Institute, China Hydropower Engineering Consulting Group Co, Changsha 410014, China; 3. School of Water Resources and Hydropower, Wuhan University, Wuhan 430072, China; 4. College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, China
  • Received:2010-03-27 Online:2011-02-10 Published:2011-02-16

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Abstract:

In light of the uncertainty of concrete dam and rock foundation parameters, a rough neural network (RNN) model is constructed and applied to interval parameters inversion of dam body and rock foundation. The RNN model is a combination of rough sets and BP-NN, which has the interval input and output just as rough sets and has a similar network structure to BP-NN. The steps of this method are as follows. Firstly, the structure is analyzed with interval finite element method. Secondly, the corresponding interval samples are chosen from interval FEM results according to special requirements for interval parameters inversion. Thirdly, the interval samples are trained continuously by RNN model until the error is less than a given threshold. Lastly, the interval parameters of dam body and rock foundation are calculated by means of network recollection and back normalization. It is shown that this method can be used to interval mechanical parameters inversion of dam body and rock foundation and the result is reasonable. Moreover, this interval analysis method based on RNN model theoretically can also be used to other interval parameters inversion after some expansion and improvement.

Key words: rough neural network, interval finite elements, interval back analysis, uncertain parameters

CLC Number: 

  • TU 452
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