Hybrid ensemble paradigms for estimating tunnel boring machine penetration rate for the 10-km long Bahce-Nurdagi twin tunnels-Reference-Cited by-同舟云学术

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Hybrid ensemble paradigms for estimating tunnel boring machine penetration rate for the 10-km long Bahce-Nurdagi twin tunnels

Published:2024-10 Issue: Volume:136 Page:108997
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Bardhan Abidhan,Tunar Ozcan Nazli,Asteris Panagiotis G.^ORCID,Gokceoglu Candan^ORCID

Publisher

Elsevier BV

Reference68 articles.

1. Fuzzy inference system-based for TBM field penetration index estimation in rock mass;Adoko;Geotech. Geol. Eng.,2019

2. Bayesian prediction of TBM penetration rate in rock mass;Adoko;Eng. Geol.,2017

3. Predicting concrete compressive strength using hybrid ensembling of surrogate machine learning models;Asteris;Cement Concr. Res.,2021

4. Hybrid ensemble soft computing approach for predicting penetration rate of tunnel boring machine in a rock environment;Bardhan;J. Rock Mech. Geotech. Eng.,2021

5. Modelling TBM performance with artificial neural networks;Benardos;Tunn. Undergr. Space Technol.,2004

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