PREDICTION OF TBM PENETRATION RATE USING SUPPORT VECTOR MACHINE

Authors

DOI:

https://doi.org/10.26895/geosaberes.v11i0.1048

Keywords:

TBM, Penetration rate, Support Vector Machine (SVM)

Abstract

One of the most important issues in mechanized excavating is to predict the TBM penetration rate. Understanding the factors influencing the rate of penetration is important, which allows for a more accurate estimation of the stopping and excavating times and operating costs. In this study, Input and output parameters including Uniaxial Compressive Strength (UCS), Brazilian Tensile Strength (BTS), Peak Slope Index (PSI), Distance between Planes of Weakness (DPW), Alpha angle and Rate of Penetration (ROP) (m/hr) in the Queens Water Tunnel using support vector machine .Results showed that prediction of penetration rate for Support Vector Machine (SVM) method is R2 = 0.9678 and RMSE = 0.064778, According to the results, Support Vector Machine (SVM) is effective and has high accuracy.

Author Biographies

  • Alireza Afradi, Islamic Azad University, Iran

    PhD Candidate, Department of Mining and Geology, Qaemshahr Branch, Islamic Azad University, Qaemshahr, Iran.

  • Arash Ebrahimabadi, Islamic Azad University, Iran

    Associate Professor, Department of Mining and Geology, Qaemshahr Branch, Islamic Azad University, Qaemshahr, Iran.

  • Tahereh Hallajian, Islamic Azad University, Iran

    Assistant Professor, Department of Mining and Geology, Qaemshahr Branch, Islamic Azad University, Qaemshahr, Iran.

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Published

2020-07-05

Issue

Vol. 11 (2020): Vol 11 (2020)

Section

Artigos

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How to Cite

PREDICTION OF TBM PENETRATION RATE USING SUPPORT VECTOR MACHINE. (2020). Geosaberes, 11, 467-479. https://doi.org/10.26895/geosaberes.v11i0.1048