期刊
PERIODICA POLYTECHNICA-CIVIL ENGINEERING
卷 60, 期 3, 页码 361-369出版社
BUDAPEST UNIV TECHNOLOGY ECONOMICS
DOI: 10.3311/PPci.7732
关键词
allowable deformation; engineering rock mass classification; orthogonal experiment; prediction; support vector machine; underground caverns
资金
- nuclear wastes major project of the State Administration of Science, Technology and Industry for National Defense (SASTIND)
This paper presents a novel allowable deformation prediction model of surrounding rock based on support vector machine (SVM). The engineering rock mass classification is subdivided based on the national standards Standard for Engineering Classification of Rock Masses in order to get more accurate physical-mechanical parameters. Using the developed parameters, 100 sets of multi-factors and multi-levels orthogonal experiments are designed, which are simulated with two-dimensional numerical models established based on ABAQUS. 100 groups of learning samples and 9 samples of random inspection are obtained. The prediction model has been established from the study of learning samples based on LibSVM. Using this model, 9 samples of random inspection and 9 engineering examples are predicted and the prediction accuracy is good compared with their actual values. It is indicated that this model can meet the initial support design requirements of underground caverns well. The novel model has the advantages of convenience, rapidity, and reliability.
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