A novel soft computing model for predicting blast - induced ground vibration in open - pit mines using gene expression programming
1 Department of Surface Mining, Mining Faculty, Hanoi University of Mining and Geology, 18 Vien st., Duc Thang ward, Bac Tu Liem dist., Hanoi, Vietnam.
2 Center for Mining, Electro - Mechanical research, Hanoi University of Mining and Geology, 18 Vien st., Duc Thang ward, Bac Tu Liem dist., Hanoi, Vietnam3 Department of Mathematical, Basic Sciences Faculty, Hanoi University of Mining and Geology, 18 Vien st., Duc Thang ward, Bac Tu Liem dist., Hanoi, Vietnam
- Keywords: Artificial intelligence;Gene expression programming; Ground vibration; Machine learning; Open - pit mine.
- Received: 25th-Aug-2020
- Revised: 24th-Sept-2020
- Accepted: 10th-Oct-2020
- Online: 15th-Oct-2020
- Section: Mining Engineering
The efforts of this study are to develop and propose a state - of - the - art model for predicting blast - induced ground vibration in open - pit mines with high accuracy anf ability based on the gene expression programming (GEP) technique. 25 blasts were conducted in the Tan Dong Hiep quarry mines with a total of 83 blasting events that were collected for this study. The GEP method was then applied to develop a non - linear equation for predicting blast - induced ground vibration based on a variety of influential parameters. A traditional empirical equation, namely Sadovski, was also applied to compare with the proposed GEP model. The results indicated that the GEP model can predict blast - induced ground vibration in open - pit mines better than the Sadovski model with an RMSE of 0.986 and R2 of 0.867. Meanwhile, the traditional empirical model (Sadovski) only provided an accuracy with an RMSE of 1.850 và R2 of 0.767.
Daniel Ainalis, Olivier Kaufmann, Jean - Pierre Tshibangu, Olivier Verlinden, và Georges Kouroussis (2017). Modelling the source of blasting for the numerical simulation of blast - induced ground vibrations: a review. Rock mechanics and rock engineering, 50(1), 171 - 193.
D Jahed Armaghani, M Hajihassani, E Tonnizam Mohamad, A Marto, và SA Noorani (2014). Blasting - induced flyrock and ground vibration prediction through an expert artificial neural network based on particle swarm optimization. Arabian Journal of Geosciences, 7(12), 5383 - 5396.
Danial Jahed Armaghani, Mohsen Hajihassani, Aminaton Marto, Roohollah Shirani Faradonbeh, và Edy Tonnizam Mohamad (2015a). Prediction of blast - induced air overpressure: a hybrid AI - based predictive model. Environmental Monitoring and Assessment, 187(11), 666.
Danial Jahed Armaghani, Mahdi Hasanipanah, Hassan Bakhshandeh Amnieh, và Edy Tonnizam Mohamad (2018). Feasibility of ICA in approximating ground vibration resulting from mine blasting. Neural Computing and Applications, 29(9), 457 - 465.
Danial Jahed Armaghani, Ehsan Momeni, Seyed Vahid Alavi Nezhad Khalil Abad, và Manoj Khandelwal (2015b). Feasibility of ANFIS model for prediction of ground vibrations resulting from quarry blasting. Environmental earth sciences, 74(4), 2845 - 2860.
Mohd Nur Asmawisham Alel, Mark Ruben Anak Upom, Rini Asnida Abdullah, và Mohd Hazreek Zainal Abidin. Optimizing Blasting’s Air Overpressure Prediction Model using Swarm Intelligence. In Journal of Physics: Conference Series, 2018 (Vol. 995, pp. 012046, Vol. 1): IOP Publishing
Nhữ Văn Bách, Bùi Xuân Nam, Nguyễn Đình An, và Trần Khắc Hùng (2012). Phương pháp xác định tốc độ dao động của nền đất khi nổ mìn vi sai phi điện. Tạp chí Khoa học kỹ thuật Mỏ - Địa chất, 38/2012, 25 - 28.
Nhữ Văn Bách, Lê Văn Quyển, Bùi Xuân Nam, Nguyễn Đình An, và Nhữ Văn Phúc (2006). Những biện pháp giảm thiểu tác dụng chấn động khi nổ mìn ở mỏ Núi Béo. Tạp chí Khoa học kỹ thuật Mỏ - Địa chất, 14/2006, 58 - 62.
Nhữ Văn Bách, Lê Văn Quyển, Lê Ngọc Ninh, và Nguyễn Đình An (2014). Công nghệ nổ mìn hiện đại với lỗ khoan đường kính lớn áp dụng cho các mỏ đá vật liệu xây dựng của Việt Nam. Hà Nội: Khoa học Tự nhiên và Công nghệ.
Xuan - Nam Bui, Yosoon Choi, Victor Atrushkevich, Hoang Nguyen, Quang - Hieu Tran, Nguyen Quoc Long, và nnk. (2020). Prediction of Blast - Induced Ground Vibration Intensity in Open - Pit Mines Using Unmanned Aerial Vehicle and a Novel Intelligence System. Natural Resources Research, 29(2), 771 - 790, doi:10.1007/s11053 - 019 - 09573 - 7.
Xuan - Nam Bui, Pirat Jaroonpattanapong, Hoang Nguyen, Quang - Hieu Tran, và Nguyen Quoc Long (2019). A novel Hybrid Model for predicting Blast - induced Ground Vibration Based on k - nearest neighbors and particle Swarm optimization. Scientific Reports, 9(1), 1 - 14.
Xuan‑Nam Bui, Hoang Nguyen, Quang Hieu Tran, Hoang‑Bac Bui, Quoc Long Nguyen, Dinh An Nguyen, và nnk. (2019). A Lasso and Elastic - Net Regularized Generalized Linear Model for Predicting Blast - Induced Air Over - pressure in Open - Pit Mines. Inżynieria Mineralna, 21.
S Ghoraba, M Monjezi, N Talebi, D Jahed Armaghani, và MR Moghaddam (2016). Estimation of ground vibration produced by blasting operations through intelligent and empirical models. Environmental earth sciences, 75(15), 1137.
Vivek K Himanshu, MP Roy, AK Mishra, Ranjit Kumar Paswan, Deepak Panda, và PK Singh (2018). Multivariate statistical analysis approach for prediction of blast - induced ground vibration. Arabian Journal of Geosciences, 11(16), 460.
M Monjezi, M Ahmadi, M Sheikhan, A Bahrami, và AR Salimi (2010). Predicting blast - induced ground vibration using various types of neural networks. Soil Dynamics and Earthquake Engineering, 30(11), 1233 - 1236.
Masoud Monjezi, M Baghestani, R Shirani Faradonbeh, M Pourghasemi Saghand, và D Jahed Armaghani (2016). Modification and prediction of blast - induced ground vibrations based on both empirical and computational techniques. Engineering with Computers, 32(4), 717 - 728.
Masoud Monjezi, Mahdi Hasanipanah, và Manoj Khandelwal (2013a). Evaluation and prediction of blast - induced ground vibration at Shur River Dam, Iran, by artificial neural network. Neural Computing and Applications, 22(7 - 8), 1637 - 1643.
Masoud Monjezi, A Mehrdanesh, A Malek, và Manoj Khandelwal (2013b). Evaluation of effect of blast design parameters on flyrock using artificial neural networks. Neural Computing and Applications, 23(2), 349 - 356.
Hoang Nguyen, Xuan - Nam Bui, Quang - Hieu Tran, và Ngoc - Luan Mai (2019). A new soft computing model for estimating and controlling blast - produced ground vibration based on hierarchical K - means clustering and cubist algorithms. Applied Soft Computing, 77, 376 - 386, doi:10.1016/j.asoc.2019.01.042.