[1]SHI Yu-chuan,JI Feng,FENG Wen-kai.Application of BP Neural Network in the Tunnel Rock Blasting[J].Research of Soil and Water Conservation,2007,14(05):242-244.
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Application of BP Neural Network in the Tunnel Rock Blasting
Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume:
14
Number of periods:
2007年05期
Page number:
242-244
Column:
Public date:
1900-01-01
- Title:
- Application of BP Neural Network in the Tunnel Rock Blasting
- Keywords:
- BP neural network; tunnel; rock burst
- CLC:
- TP813
- DOI:
- -
- Abstract:
- Four diversion tunnels and two parallel traffic tunnels to be constructed in a hydropower of Southwest,but the buried deep in the project area is 1 000～2 000 m in general,the largest is 2 525 m,which located in the high stress zone,now excavation hole of the 2 000 m are found in the low to medium rock burst phenomenon,therefore,rock burst intensity of the tunnel is very sensitive in subsequent excavation in the deep,long and big conditions,using BP artificial neural network established a burst prediction models which includes strength brittleness factor,stress factors such as elements of the eight indicators,achieved 12 200 m support for the forthcoming excavation hole of a forecast.The results showed that the effect of this forecasting methods is good,and coincide with the geological analysis judgement,which can be used for further guidance practice.
- References:
-
[1] (GB50287-99)水利水电工程地质勘察规范[S].
[2] 徐则明, 黄润秋.深埋特长隧道及其施工地质灾害[M].成都:西南交通大学出版社, 2000.
[3] 谭以安.模糊数学综合评判在地下洞室岩爆预测中的应用[A].第二次全国岩石力学与工程学术会议论文集[C].北京:知识出版社, 1989.
[4] 杨健, 武雄.岩爆综合预测评价方法[J].岩石力学与工程学报, 2005, 24(3):411-416.
[5] 汪培庄, 韩立岩.应用模糊数学[M].北京经济学院出版社, 1989.
[8] 唐礼忠, 王文星.一种新的岩爆倾向性指标[J].岩石力学与工程学报, 2002, 21(6):874-878.
- Similar References:
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Last Update:
1900-01-01