The prediction of EPB-TBM performance using firefly algorithms and particle swarm optimization

Authors

DOI:

https://doi.org/10.17794/rgn.2023.5.7

Keywords:

EPB-TBM, penetration rate, regression, firefly algorithm, particle swarm optimization

Abstract

Penetration rate is one of the most important parameters in determining excavation time in tunnelling operations. Providing a prediction model or a mathematical relationship can give a better understanding of this issue. A mathematical equation between input and output parameters can be optimized by using algorithms such as Particle Swarm Optimization and Firefly. Since drilling operations interact between ground and machine, therefore, the effective parameters on the penetration rate are divided into two general categories such as machine and geological factors. Effective geological factors include internal friction angle, cohesion, specific gravity, shear modulus and groundwater level. In addition, the important parameters of TBM are torque, thrust jacks, and rotation speed. By defining an initial mathematical function, two optimization algorithms, which look for the most optimal mode, the goal here is the same as the mean square error (MSE). Finally, by examining and comparing the performance of two algorithms, using the coefficient of determination and the mean square error, it found that the Firefly algorithm has a better performance than the Particle Swarm Optimization algorithm.

Downloads

Published

2023-12-04

How to Cite

Khoshzaher, E., Chakeri, H., Bazargan, S., & Mousapour, H. (2023). The prediction of EPB-TBM performance using firefly algorithms and particle swarm optimization. Rudarsko-geološko-Naftni Zbornik, 38(5), 79–86. https://doi.org/10.17794/rgn.2023.5.7

Issue

Vol. 38 No. 5 (2023): No. 66

Section

Mining

License

Copyright (c) 2023 Hamid Chakeri, Erfan Khoshzaher, Shahab Bazargan, hamid mousapour

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Creative Commons-BY

Authors who publish with this journal agree to the following terms:

In agreeing this form, you certify that:

  1. You read the ethical codex of the RGN zbornik available at journal web.
  2. You submitted work is your original work, and has not previously been published and does not include any form of plagiarism.
  3. You own copyright in the submitted work, and are therefore permitted to assign the licence to publish to RGN zbornik.
  4. Your submitted work contains no violation of any existing copyright or other third party right or any material of an obscene, libellous or otherwise unlawful nature.
  5. You have obtained permission for and acknowledged the source of any illustrations, diagrams or other material included in the work of which you are not the copyright owner.
  6. You have taken due care to ensure the accuracy of the work, and that, to the best of your knowledge, there are no false statements made within it.
  7. All co-authors of this submitted work are aware of, and in agreement with, the terms of this licence and that the submitted manuscript has been approved by these authors.

 

Publication licence

You retain copyright in your submitted work, according to journal license policy (CC-BY). By signing this form you agree that RGN zbornik may publish it under the publication licence. In summary the licence allows the following:

Anyone is free:

  • To copy, distribute, display, and perform the work.
  • To make derivative works.

 

Under the following conditions:

  • The original author must always be given credit.
  • The work may not be used for commercial purposes.
  • If the work is altered, transformed, or built upon, the resulting work may only be distributed under a licence identical to this one.

 

Exceptions to the licence

In addition to publishing the work printed under the above licence, RGN zbornik will also enable the work to be visible online.

The journal editorial can change the licence rules anytime but it cannot retroactively restrict author(s) rights.