Techno Press
You logged in as Techno Press

Geomechanics and Engineering
  Volume 30, Number 6, September25 2022 , pages 489-502

Meta-heuristic optimization algorithms for prediction of fly-rock in the blasting operation of open-pit mines
Arsalan Mahmoodzadeh, Hamid Reza Nejati, Mokhtar Mohammadi, Hawkar Hashim Ibrahim, Shima Rashidi and Adil Hussein Mohammed

    In this study, a Gaussian process regression (GPR) model as well as six GPR-based metaheuristic optimization models, including GPR-PSO, GPR-GWO, GPR-MVO, GPR-MFO, GPR-SCA, and GPR-SSO, were developed to predict fly-rock distance in the blasting operation of open pit mines. These models included GPR-SCA, GPR-SSO, GPR-MVO, and GPR. In the models that were obtained from the Soungun copper mine in Iran, a total of 300 datasets were used. These datasets included six input parameters and one output parameter (fly-rock). In order to conduct the assessment of the prediction outcomes, many statistical evaluation indices were used. In the end, it was determined that the performance prediction of the ML models to predict the fly-rock from high to low is GPR-PSO, GPR-GWO, GPR-MVO, GPR-MFO, GPR-SCA, GPR-SSO, and GPR with ranking scores of 66, 60, 54, 46, 43, 38, and 30 (for 5-fold method), respectively. These scores correspond in conclusion, the GPR-PSO model generated the most accurate findings, hence it was suggested that this model be used to forecast the fly-rock. In addition, the mutual information test, also known as MIT, was used in order to investigate the influence that each input parameter had on the fly-rock. In the end, it was determined that the stemming (T) parameter was the most effective of all the parameters on the fly-rock.
Key Words
    fly-rock; hybrid models; machine learning; metaheuristic optimization; sensitivity analysis
Arsalan Mahmoodzadeh: Rock Mechanics Division, School of Engineering, Tarbiat Modares University, Tehran, Iran
Hamid Reza Nejati: Rock Mechanics Division, School of Engineering, Tarbiat Modares University, Tehran, Iran
Mokhtar Mohammadi: Department of Information Technology, College of Engineering and Computer Science, Lebanese French University, Kurdistan Region, Iraq
Hawkar Hashim Ibrahim: Department of Civil Engineering, College of Engineering, Salahaddin University-Erbil, 44002 Erbil, Kurdistan Region, Iraq
Shima Rashidi: Department of Computer Science, College of Science and Technology, University of Human Development,
Sulaymaniyah, Kurdistan Region, Iraq
Adil Hussein Mohammed: Department of Communication and Computer Engineering, Faculty of Engineering, Cihan University-Erbil, Kurdistan Region, Iraq

Techno-Press: Publishers of international journals and conference proceedings.       Copyright © 2022 Techno Press
P.O. Box 33, Yuseong, Daejeon 305-600 Korea, Tel: +82-42-828-7996, Fax : +82-42-828-7997, Email: