[1] |
LIU Q, HUANG X, GONG Q, et al. Application and development of hard rock TBM and its prospect in China[J]. Tunnelling and Underground Space Technology, 2016, 57: 33-46.
|
[2] |
唐彬,王传兵.立井煤矿硬岩TBM施工巷道支护设计技术[J].煤炭工程,2015,47(12): 31-33+37.
|
[3] |
温森, 赵延喜, 杨圣奇. 基于Monte Carlo-BP神经网络TBM掘进速度预测[J]. 岩土力学, 2009,30(10): 3127-3132.
|
[4] |
王健, 王瑞睿, 张欣欣, 等. 基于RMR岩体分级系统的TBM掘进性能参数预测[J]. 隧道建设(中英文), 2017, 37(06): 700-707.
|
[5] |
闫长斌, 杜旭阳, 戴晓亚, 等. 基于围岩力学参数的TBM净掘进速率多元回归预测模型[J]. 隧道建设(中英文), 2019, 39(01): 48-53.
|
[6] |
L O. Development of theoretical equations for predicting tunnel borability[D]. Golden: Colorado School of Mines, 1977.
|
[7] |
A B. Hard rock tunnel boring[D]. Trondheim: Norwegian University of Science and Technology, 1998.
|
[8] |
YAGIZ S. Utilizing rock mass properties for predicting TBM performance in hard rock condition[J]. Tunnelling & Underground Space Technology Incorporating Trenchless Technology Research, 2008,23(3): 326-339.
|
[9] |
YAGIZ S, GOKCEOGLU C, SEZER E, et al. Application of two non-linear prediction tools to the estimation of tunnel boring machine performance[J]. Engineering Applications of Artificial Intelligence, 2009,22(4-5): 808-814.
|
[10] |
YAGIZ S, KARAHAN H. Prediction of hard rock TBM penetration rate using particle swarm optimization[J]. International Journal of Rock Mechanics & Mining ences, 2011,48(3): 427-433.
|
[11] |
KOOPIALIPOOR M, TOOTOONCHI H, ARMAGHANI D J, et al. Application of deep neural networks in predicting the penetration rate of tunnel boring machines[J]. Bulletin of Engineering Geology and the Environment, 2019,78(8): 6347-6360.
|
[12] |
张德丰. MATLAB概率与数理统计分析[M]. 机械工业出版社, 2010.
|
[13] |
SEBASTIANI M R D S. Artificial Intelligence to predict Maximum Surface Settlements induced by Mechanized Tunnelling[J]. Springer Nature Switzerland AG, 2019,40: 490-499.
|
[14] |
昝军才,魏成才,蒋可娟,吴雨欣,袁超.基于BP神经网络的煤自燃温度预测研究[J].煤炭工程,2019,51(10): 113-117.
|
[15] |
薛黎明,张心智,刘保康,胡雅各.基于支持向量回归机的河北省能源消费碳排放预测[J].煤炭工程,2017,49(08): 165-168.
|
[16] |
井彦林, 仵彦卿, 林杜军, 等. 黄土的湿陷性与击实试验指标关系研究[J]. 岩土力学, 2011(02): 393-397.
|
[17] |
ZORLU K, GOKCEOGLU C, OCAKOGLU F, et al. Prediction of uniaxial compressive strength of sandstones using petrography-based models[J]. Engineering Geology, 2008,96(3-4): 141-158.
|