A reduction policy of ground vibration due to mine blasting using hybrid algorithms

Document Type : Research Paper

Authors

Department of Engineering, Tarbiat Modares University, Tehran, Iran.

10.22059/ijmge.2026.399055.595281

Abstract

Blast-induced ground vibration poses significant environmental and safety challenges in mining operations. Traditional predictive models relying on Peak Particle Velocity (PPV) face limitations due to the confounding effect of distance, a non-controllable variable. This study introduces a novel integrated framework for predicting and optimizing blast vibrations through four key contributions. First, we propose the Vibration Power Index (VPI = PPV × D^α), a location-independent metric derived from seismic attenuation laws with an empirically determined site-specific coefficient. Second, to address data scarcity, we implement SMOTER (Synthetic Minority Over-sampling Technique for Regression) for enhanced dataset augmentation. Third, we develop a robust Artificial Neural Network (ANN) model for VPI prediction, which is subsequently integrated with an enhanced Hybrid Firefly Algorithm (HFA) featuring chaotic initialization and adaptive parameters for global optimization. Finally, a closed-loop methodology from data preprocessing to optimization was established. Applied to 77 blast records from the Asbcheran mine, our ANN achieved superior performance (R²=0.97, RMSE=4.33), while the HFA identified an optimal pattern reducing mean VPI by 28%. This framework provides a practical tool for sustainable blast design optimization.

Keywords

Main Subjects

References

[1]. Kazemi, M. M. K., Nabavi, Z., Rezakhah, M., & Masoudi, A. (2023). Application of XGB-based metaheuristic techniques for prediction time-to-failure of mining machinery. Systems and Soft Computing, 5, 200061.
[2]. Moreno, E., Ferreira, F., Goycoolea, M., Espinoza, D., Newman, A., & Rezakhah, M. (2015). Linear programming approximations for modeling instant-mixing stockpiles. In Application of computers and operations research in the mineral industry-proceedings of the 37th international symposium, APCOM (Vol. 2009, pp. 582-587).
[3]. Mirzehi, M., Rezakhah, M., Mousavi, A., & Nabavi, Z. (2023). New MIP model for short-term planning in open-pit mines considering loading machine performance: a case study in Iran. International Journal of Mining and Mineral Engineering, 14(4), 341-364.
[5]. Khajevand, S., Rezakhah, M., Monjezi, M., & Manríquez León, F. A. (2025). Enhancing Transportation Fleet Efficiency in Open-Pit Mining via Simulation: a Case Study. Journal of Mining and Environment, 16(3), 997-1007.
[6]. Rezakhah, M., & Moreno, E. (2019, November). Open pit mine scheduling model considering blending and stockpiling. In International Symposium on Mine Planning & Equipment Selection (pp. 75-82). Cham: Springer International Publishing.
[7]. Rezakhah, M. Optimizing Blast-Induced Ground Vibration Reduction Using an Integrated ANN-EOA Model: A Case Study of Sarcheshmeh Copper Mine.
[8]. Nemati Vardin, A., Monjezi, M., Amini Khoshalan, H., Hamidi Khademi, J., & Rezakhah, M. (2025). Application of intelligent methods in predicting penetration rate of drill bits in open-pit mining. Journal of Mining and Environment.
[9]. Hayati, M., Sayadi, A. R., Monjezi, M., & Rezakhah, M. (2025). Managing risk in tunneling projects: A fuzzy TOPSIS approach for improved decision-making.
[10]. Rezakhah, M., Nemati, E., Batarbiat, A., & Khandelwal, M. (2025). Integrating ANN Prediction with Honeybee Optimisation for Flyrock Minimisation in Open-Pit Mining. Rudarsko-geološko-naftni zbornik, 40(5), 141-152.
[11]. Monjezi, M., Goshtasbi, K., Rezakhah, M., & Singh, T. N. (2007). Design of stable slopes for Songun copper mine. Mining Technology, 116(3), 146-152.
[12]. Tajik, S., Monjezi, M., Rezakhah, M., & Amiri Hosseini, M. (2023). Development of a Mathematical Model for Predicting Blast-Induced Fragmentation Considering Elastic Wave Velocities. JOURNAL OF ROCK MECHANICS, 7(2), 71-82.
[13].  Afeni, T. B., & Osasan, S. K. (2009). Assessment of noise and ground vibration induced during blasting operations in an open pit mine—a case study on Ewekoro limestone quarry, Nigeria. Mining Science and Technology (China), 19(4), 420-424.
[14]. Singh, T. N., & Singh, V. (2005). An intelligent approach to prediction and control ground vibration in mines. Geotechnical & Geological Engineering, 23, 249-262.
[15]. Khandelwal, M., & Singh, T. N. (2009). Prediction of blast-induced ground vibration using artificial neural network. International Journal of Rock Mechanics and Mining Sciences, 46(7), 1214-1222.
[16].  R.Ostovar, Blasting in mines., Vol.2, 1994: Publication of JIHAD Amirkabir University
[17].  Jimeno, C. L., Jimeno, E. L., Carcedo, F. J. A., & de Ramiro, Y. V. (1995). Drilling änd blasting of rocks. USA CRS Press, 41, 35947.
[18]. Roy, P. P. (1998). Technical Note Characteristics of ground vibrations and structural response to surface and underground blasting. Geotechnical & Geological Engineering, 16, 151-166.
[19]. Hudaverdi, T. (2012). Application of multivariate analysis for prediction of blast-induced ground vibrations. Soil Dynamics and Earthquake Engineering, 43, 300-308.
[20]. Khandelwal, M., & Singh, T. N. (2006). Prediction of blast induced ground vibrations and frequency in opencast mine: a neural network approach. Journal of sound and vibration, 289(4-5), 711-725.
[21]. Monjezi, M., Ghafurikalajahi, M., & Bahrami, A. (2011). Prediction of blast-induced ground vibration using artificial neural networks. Tunnelling and underground space technology, 26(1), 46-50.
[22]. M, Ganjalivand., Estimation of ground vibration in surface blasting based on Geomechanical and Geophysical properties of rock mass (case study: Choghart mine).,2016., Yazd University
[23]. Lallart, M. (Ed.). (2010). Vibration control. BoD–Books on Demand.
[24]. Indian Standard, I., Criteria for Safety and Design of Structures Subjected to Underground Blast. Bulletin No: IS-6922, Bureau of Indian Standards, New Delhi, India, 1973.
[25]. New, B. M. (1986). Ground vibration caused by civil engineering works (No. RR 53).
[26]. Ozer, U., Karadogan, A., Kahriman, A., & Aksoy, M. (2011). Bench blasting design based on site-specific attenuation formula in a quarry. Arab J Geosci 6: 711–721.
[27]. Iphar, M., Yavuz, M., & Ak, H. (2008). Prediction of ground vibrations resulting from the blasting operations in an open-pit mine by adaptive neuro-fuzzy inference system. Environmental geology, 56, 97-107.
[28]. Amnieh, H. B., Mozdianfard, M. R., & Siamaki, A. (2010). Predicting of blasting vibrations in Sarcheshmeh copper mine by neural network. Safety Science, 48(3), 319-325.
[29]. Armaghani, D. J., Hajihassani, M., Mohamad, E. T., Marto, A., & Noorani, S. A. (2014). Blasting-induced flyrock and ground vibration prediction through an expert artificial neural network based on particle swarm optimization. Arabian Journal of Geosciences, 7, 5383-5396.
[30]. Hajihassani, M., Jahed Armaghani, D., Monjezi, M., Mohamad, E. T., & Marto, A. (2015). Blast-induced air and ground vibration prediction: a particle swarm optimization-based artificial neural network approach. Environmental Earth Sciences, 74, 2799-2817.
[31]. Saadat, M., Hasanzade, A., & Khandelwal, M. (2015). Differential evolution algorithm for predicting blast induced ground vibrations. International Journal of Rock Mechanics and Mining Sciences, 77, 97-104.
[32]. Bayat, P., Monjezi, M., Rezakhah, M., & Armaghani, D. J. (2020). Artificial neural network and firefly algorithm for estimation and minimization of ground vibration induced by blasting in a mine. Natural Resources Research, 29, 4121-4132.
[33]. Shang, Y., Nguyen, H., Bui, X. N., Tran, Q. H., & Moayedi, H. (2020). A novel artificial intelligence approach to predict blast-induced ground vibration in open-pit mines based on the firefly algorithm and artificial neural network. Natural Resources Research, 29(2), 723-737.
[34]. Chen, W., Hasanipanah, M., Nikafshan Rad, H., Jahed Armaghani, D., & Tahir, M. M. (2021). A new design of evolutionary hybrid optimization of SVR model in predicting the blast-induced ground vibration. Engineering with Computers, 37, 1455-1471.
International Journal of Mining and Geo-Engineering
Volume 60, Issue 1
March 2026
Pages 35-42

Files

Share

How to cite

Statistics