TY  - GEN
AB  - This book covers the tunnel boring machine (TBM) performance classifications, empirical models, statistical and intelligent-based techniques which have been applied and introduced by the researchers in this field. In addition, a critical review of the available TBM performance predictive models will be discussed in details. Then, this book introduces several predictive models i.e., statistical and intelligent techniques which are applicable, powerful and easy to implement, in estimating TBM performance parameters. The introduced models are accurate enough and they can be used for prediction of TBM performance in practice before designing TBMs.
AU  - Armaghani, Danial Jahed,
AU  - Azizi, Aydin,
CN  - TA815
DO  - 10.1007/978-981-16-1034-9
DO  - doi
ID  - 1435170
KW  - Tunneling
KW  - Artificial intelligence
KW  - Tunnels
KW  - Intelligence artificielle
LK  - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-16-1034-9
N2  - This book covers the tunnel boring machine (TBM) performance classifications, empirical models, statistical and intelligent-based techniques which have been applied and introduced by the researchers in this field. In addition, a critical review of the available TBM performance predictive models will be discussed in details. Then, this book introduces several predictive models i.e., statistical and intelligent techniques which are applicable, powerful and easy to implement, in estimating TBM performance parameters. The introduced models are accurate enough and they can be used for prediction of TBM performance in practice before designing TBMs.
SN  - 9789811610349
SN  - 9811610347
T1  - Applications of artificial intelligence in tunnelling and underground space technology /
TI  - Applications of artificial intelligence in tunnelling and underground space technology /
UR  - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-16-1034-9
ER  -