Please use this identifier to cite or link to this item: https://doi.org/10.1016/S0045-7949(03)00303-1
Title: Neural identification of rock parameters using fuzzy adaptive learning parameters
Authors: Liang, Y.C.
Feng, D.P.
Liu, G.R. 
Yang, X.W. 
Han, X. 
Keywords: Artificial neural networks
Fuzzy back-propagation algorithm
Inverse analysis
Parameter identification
Rock engineering
Issue Date: Sep-2003
Source: Liang, Y.C., Feng, D.P., Liu, G.R., Yang, X.W., Han, X. (2003-09). Neural identification of rock parameters using fuzzy adaptive learning parameters. Computers and Structures 81 (24-25) : 2373-2382. ScholarBank@NUS Repository. https://doi.org/10.1016/S0045-7949(03)00303-1
Abstract: An improved fuzzy adaptive back-propagation algorithm is proposed and applied to the identification of mechanical parameters of the surrounding rock of underground caverns in stratified layers. The improved algorithm adopts some advanced ideas and techniques from computational intelligence, and combines the fuzzy theory with artificial neural network techniques and the mutation strategy in genetic algorithms. The improved algorithm extends the effectiveness and the adaptivity of the Fuzzy BP algorithm. The successful estimates of mechanical parameters and the initial stresses in the surrounding rock show that a feasible method of identification is provided, which can be used to identify parameters in rock engineering quickly and effectively. © 2003 Elsevier Ltd. All rights reserved.
Source Title: Computers and Structures
URI: http://scholarbank.nus.edu.sg/handle/10635/60878
ISSN: 00457949
DOI: 10.1016/S0045-7949(03)00303-1
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