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|Title:||Neural identification of rock parameters using fuzzy adaptive learning parameters||Authors:||Liang, Y.C.
|Keywords:||Artificial neural networks
Fuzzy back-propagation algorithm
|Issue Date:||Sep-2003||Citation:||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|
|Appears in Collections:||Staff Publications|
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