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Paper Information

Title: 

PREDICTION OF TBM PENETRATION RATE BY USING NEURAL NETWORK

Type: PAPER
Author(s): YAVARI MAHDI*,MAHDIVARI S.
 
 *MINING DEPARTMENT, ENGINEERING FACULTY, TEHRAN UNIVERSITY, IRAN
 
Name of Seminar: PROCEEDING OF IRANIAN MINING ENGINEERING CONFERENCE
Type of Seminar:  CONFERENCE
Sponsor:  IRANIAN SOCIETY OF MINING ENGINEERING
Date:  2005Volume 1
 
 
Abstract: 

In this article at first some models of penetration rate prediction are reviewed then a neural network is created for prediction of penetration rate. The neural network inputs are Rock Type, UCS, RQD, Normal force on disc cutters, Diameter of disc cutters and Quartz content. By eliminating quartz content and RQD from input parameters the response of the neural network is investigated. The neural network response in Comparison with the Garaham model, ability of the neural network in prediction of penetration rate and prediction of penetration rate for the Gavoshan tunnel's TBM are discussed in the latest parts of the article.   

 
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