Discussion on the paper “Success and challenges in predicting TBM penetration rate using recurrent neural networks” by Feng Shan, Xuzhen He, Danial Jahed Armaghani, Pin Zhang, Daichao Sheng

Georg H. Erharter; Thomas Marcher

doi:10.1016/j.tust.2023.105063

Discussion on the paper “Success and challenges in predicting TBM penetration rate using recurrent neural networks” by Feng Shan, Xuzhen He, Danial Jahed Armaghani, Pin Zhang, Daichao Sheng

Georg H. Erharter^*, Thomas Marcher

^*Korrespondierende/r Autor/-in für diese Arbeit

Institut für Felsmechanik und Tunnelbau (2200)

Publikation: Beitrag in einer Fachzeitschrift › Diskussion › Begutachtung

Originalsprache	englisch
Aufsatznummer	105063
Fachzeitschrift	Tunnelling and Underground Space Technology
Jahrgang	135
DOIs	https://doi.org/10.1016/j.tust.2023.105063
Publikationsstatus	Veröffentlicht - Mai 2023

ASJC Scopus subject areas

Bauwesen
Geotechnik und Ingenieurgeologie

Zugriff auf Dokument

10.1016/j.tust.2023.105063

Andere Dateien und Links

Verknüpfung zur Publikation in Scopus

Dieses zitieren

Discussion on the paper “Success and challenges in predicting TBM penetration rate using recurrent neural networks” by Feng Shan, Xuzhen He, Danial Jahed Armaghani, Pin Zhang, Daichao Sheng. / Erharter, Georg H.; Marcher, Thomas.
in: Tunnelling and Underground Space Technology, Jahrgang 135, 105063, 05.2023.

Publikation: Beitrag in einer Fachzeitschrift › Diskussion › Begutachtung

@article{9029f4f5befa47ef853eef0f3175b9b0,

title = "Discussion on the paper “Success and challenges in predicting TBM penetration rate using recurrent neural networks” by Feng Shan, Xuzhen He, Danial Jahed Armaghani, Pin Zhang, Daichao Sheng",

keywords = "Plausibility, Reproducibility, Rockmass prediction, TBM operational data, Time delayed prediction",

author = "Erharter, {Georg H.} and Thomas Marcher",

year = "2023",

month = may,

doi = "10.1016/j.tust.2023.105063",

language = "English",

volume = "135",

journal = "Tunnelling and Underground Space Technology",

issn = "0886-7798",

publisher = "Elsevier Limited",

}

TY - JOUR

T1 - Discussion on the paper “Success and challenges in predicting TBM penetration rate using recurrent neural networks” by Feng Shan, Xuzhen He, Danial Jahed Armaghani, Pin Zhang, Daichao Sheng

AU - Erharter, Georg H.

AU - Marcher, Thomas

PY - 2023/5

Y1 - 2023/5

KW - Plausibility

KW - Reproducibility

KW - Rockmass prediction

KW - TBM operational data

KW - Time delayed prediction

UR - http://www.scopus.com/inward/record.url?scp=85149927230&partnerID=8YFLogxK

U2 - 10.1016/j.tust.2023.105063

DO - 10.1016/j.tust.2023.105063

M3 - Comment/debate

AN - SCOPUS:85149927230

SN - 0886-7798

VL - 135

JO - Tunnelling and Underground Space Technology

JF - Tunnelling and Underground Space Technology

M1 - 105063

ER -