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Artificial Intelligence Based Smart Blasting Using ICA Optimized Neural Network for Oversize Prediction in a Small Scale Dolomite Quarry in Nigeria Artificial Intelligence Based Smart Blasting Using ICA Optimized Neural Network for Oversize Prediction in a Small Scale Dolomite Quarry in Nigeria
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Open Access Research Article

Artificial Intelligence Based Smart Blasting Using ICA Optimized Neural Network for Oversize Prediction in a Small Scale Dolomite Quarry in Nigeria

by Blessing Olamide Taiwo 1,* ,  Abduljeleel Ibidapo Ajibona 1 ,  Angesom Gebrestsadik 2,3,* ,  Oluwaseun Victor F amobuwa 4 ,  Ojo Augustine Thomas 4  and  Akinwale O Omosebi 1
1
Department of Mining Engineering, Federal University of Technology, Akure, Nigeria
2
Division of Sustainable Resources Engineering, Graduate School of Engineering, Hokkaido University, Sapporo, Japan
3
Department of Mining Engineering, Aksum University, Aksum, Tigray, Ethiopia
4
Department of Mining Engineering, West Virginia University, USA
*
Author to whom correspondence should be addressed.
RML  2025 2(2):18; https://doi.org/10.70425/rml.202502.18
Received: 21 May 2025 / Accepted: 25 June 2025 / Published Online: 29 June 2025
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Abstract

Abstract The integration of artificial intelligence (AI) into blasting operations has demonstrated significant improvements in precision, safety, and operational efficiency. By leveraging AI algorithms to optimize blast design, monitor field conditions, and analyze fragmentation data, more informed decision-making is achieved. In small-scale mining, safe and efficient blasting practices are critical to protecting workers, maximizing resource extraction, and minimizing environmental impacts. This study first reviews the applications, advantages, and limitations of various AI techniques used in predicting blast performance and environmental effects, with specific attention to the overlooked impact of multicollinearity and the absence of explicit mathematical expressions in many soft computing models. In the experimental section, an imperialist competitive algorithm (ICA)-optimized artificial neural network (ANN) model is developed to predict the percentage of oversized material produced by small-scale blasting. Field data, including blast parameters and rock strength, were collected from a dolomite quarry in Akoko, Edo State, Nigeria. Fragmentation analysis was conducted using WipFrag 4.0 software across 48 blast rounds, using the primary crusher gape as the decision threshold. Input parameter selection was guided by multicollinearity analysis to ensure robust modeling. Evaluation metrics such as root-mean-square error (RMSE), correlation coefficient (R²), mean absolute percentage error (MAPE), variance accounted for (VAF), Nash–Sutcliffe efficiency (NSE), and performance index (PI) confirmed that the ICA-ANN model significantly outperformed the standard ANN. While the conventional ANN model underestimated oversize by 14.7%, the ICA-ANN achieved a lower prediction error of 2.7%. The proposed model offers a practical and accurate tool for predicting oversized fragmentation in small-scale rock engineering scenarios, contributing to improved blasting efficiency and sustainability in the mining sector.

Keywords: Mining; Rock fragmentation; Blast optimization; Artificial intelligence (AI); Multicollinearity; Imperialist competitive algorithm (ICA); Artificial neural network (ANN);
Copyright: © 2025 by Taiwo, Ajibona, Gebrestsadik, amobuwa, Thomas and Omosebi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (Creative Commons Attribution 4.0 International License). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
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ACS Style
Taiwo, B. O.; Ajibona, A. I.; Gebrestsadik, A.; amobuwa, O. V. F.; Thomas, O. A.; Omosebi, A. O. Artificial Intelligence Based Smart Blasting Using ICA Optimized Neural Network for Oversize Prediction in a Small Scale Dolomite Quarry in Nigeria. Rock Mechanics Letters, 2025, 2, 18. doi:10.70425/rml.202502.18
AMA Style
Taiwo B O, Ajibona A I, Gebrestsadik A et al.. Artificial Intelligence Based Smart Blasting Using ICA Optimized Neural Network for Oversize Prediction in a Small Scale Dolomite Quarry in Nigeria. Rock Mechanics Letters; 2025, 2(2):18. doi:10.70425/rml.202502.18
Chicago/Turabian Style
Taiwo, Blessing O.; Ajibona, Abduljeleel I.; Gebrestsadik, Angesom; amobuwa, Oluwaseun V. F.; Thomas, Ojo A.; Omosebi, Akinwale O. 2025. "Artificial Intelligence Based Smart Blasting Using ICA Optimized Neural Network for Oversize Prediction in a Small Scale Dolomite Quarry in Nigeria" Rock Mechanics Letters 2, no.2:18. doi:10.70425/rml.202502.18
APA Style
Taiwo, B. O., Ajibona, A. I., Gebrestsadik, A., amobuwa, O. V. F., Thomas, O. A., & Omosebi, A. O. (2025). Artificial Intelligence Based Smart Blasting Using ICA Optimized Neural Network for Oversize Prediction in a Small Scale Dolomite Quarry in Nigeria. Rock Mechanics Letters, 2(2), 18. doi:10.70425/rml.202502.18

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