ISSN 2096-4498
CN 44-1745/U
Tunnel Construction ›› 2013, Vol. 33 ›› Issue (11): 903-907.DOI: 10.3973/j.issn.1672-741X.2013.11.002
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ZHOU Xiancang
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The accuracy of rock mass classification has close relationship with the safety and cost of tunnel construction. Due to the disadvantages of the present rock mass classification methods, a new rock mass classification method based on radial basis function neural network is introduced on basis of the national BQ rock mass classification standard,a large number of site measurements and indoor tests, as well as the rock mass classification practice made in the construction of the tunnel group on NinguoJixi highway. The classification results are served as the training samples for geneticRBF neural network training. Therefore, the intelligent classification model is established after network training has been finished. The application of this model shows that the result of the classification made on basis of the geneticRBF neural network agrees with that made on basis of site reconnaissance. The geneticRBF neural network developed provides a new approach for the classification of surrounding rock mass of tunnels.
Key words: tunnel engineering, surrounding rock mass classification, radial basis function, neural network, genetic algorithm
ZHOU Xiancang. A New Classification Method for Rock Mass of Highway Tunnels Based on GeneticRadial Basis Function Neural Network[J]. Tunnel Construction, 2013, 33(11): 903-907.
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URL: http://www.suidaojs.com/EN/10.3973/j.issn.1672-741X.2013.11.002
http://www.suidaojs.com/EN/Y2013/V33/I11/903
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