Prediction of hard rock TBM penetration rate based on Data Mining techniques

The aim of this work is to use Data Mining tools to develop models for the prediction of hard rock tunnel boring machine (TBM) penetration rate (ROP). A database published by Yagiz (2008) was used to develop these models. The parameters of the database were the uniaxial compressive strength (UCS), a...

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Bibliographic Details
Main Author: Martins, Francisco F. (author)
Other Authors: Miranda, Tiago F. S. (author)
Format: conferencePaper
Language:eng
Published: 2013
Subjects:
Tunnel boring machine
Penetration ratio
Data mining
Machine learning
Online Access:http://hdl.handle.net/1822/25941
Country:Portugal
Oai:oai:repositorium.sdum.uminho.pt:1822/25941

Internet

http://hdl.handle.net/1822/25941

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