中南大学 资源与安全工程学院,长沙,410083
纸质出版:2009
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史秀志, 周健. 隧道围岩分级判别的未确知均值聚类模型[J]. 土木与环境工程学报(中英文), 2009,31(2):62-67.
SHI Xiuzhi, ZHOU Jian. Application of Uncertainty Average Clustering Measurement Model to Classification of Tunnel Surrounding Rock[J]. Journal of Civil and Environmental Engineering, 2009, 31(2): 62-67.
史秀志, 周健. 隧道围岩分级判别的未确知均值聚类模型[J]. 土木与环境工程学报(中英文), 2009,31(2):62-67. DOI: 10.11835/j.issn.1674-4764.2009.02.012.
SHI Xiuzhi, ZHOU Jian. Application of Uncertainty Average Clustering Measurement Model to Classification of Tunnel Surrounding Rock[J]. Journal of Civil and Environmental Engineering, 2009, 31(2): 62-67. DOI: 10.11835/j.issn.1674-4764.2009.02.012.
基于未确知测度理论,建立隧道围岩分级的未确知均值聚类分析模型。针对隧道围岩分级判别中等级评价中许多不确定性影响因素,选用岩石等级、风化程度、岩体弹性纵波波速、岩体结构、地质构造影响程度、节理裂隙发育程度和地下水情况等7个指标作为隧道围岩分级的判别因子;以20组隧道围岩实测数据作为训练样本,建立各评价因子的未确知测度函数,用各分类样本平均值表示其分类中心;根据信息熵理论计算各评价因子的权重,依照置信度识别准则进行等级判定;用建立的模型对20组实测数据逐一进行回检,正确率为100%。将建立的模型对待分类的10
Based on the uncertainty measurement theory
a uncertainty average clustering measurement model for tunnel surrounding rock classification was established. Due to the uncertain factors in judging the engineering quality of rock masses
seven indexes
i.e.
the rock grade
rock weathering degree
rock mass structure
elasticity longitudinalwave velocity of rock mass
influence degree of geological structure
development of joint fissure and ground water regime
were used as the discriminating factors. the indexes functions of unascertained measurement of 20 sets of rock samples were established
and the centre of the classification was indicated by using the average of classification of samples. The weight of indexes was calculated by entropy weight theory
and a prediction for the classification of residual tunnel surrounding rock was carried out using the rules of credible recognition. Each of the 20 sets of tunnel surrounding rockmass samples was tested according to the model
and the correctness rate is 100%. The other 10 sets of tunnel surrounding rock samples were predicted by using this model. The results show that the uncertainty measurement model classification agrees well with the actual measured ones. Therefore
it shows that the uncertaity measurement model is effective
available and can be applied to classification of tunnel surrounding rock in underground engineering.
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