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A comparison of advanced computational models and experimental techniques in predicting blast-induced ground vibration in open-pit coal mine

  • Research Article - Solid Earth Sciences
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Abstract

Green mining is an essential requirement for the development of the mining industry. Of the operations in mining technology, blasting is one of the operations that significantly affect the environment, especially ground vibration. In this paper, four artificial intelligence (AI) models including artificial neural network (ANN), k-nearest neighbor (KNN), support vector machine (SVM), and classification and regression tree (CART) were developed as the advanced computational models for estimating blast-induced ground vibration in a case study of Vietnam. Some empirical techniques were applied and developed to predict ground vibration and compared with the four AI models as well. For this research, 68 events of blasting were collected; 80% of the whole datasets were used to build the mentioned models, and the rest 20% were used for testing/checking the models’ performances. Mean absolute error (MAE), determination coefficient (R2), and root-mean-square error (RMSE) were used as the standards to evaluate the quality of the models in this study. The results indicated that the advanced computational models were much better than empirical techniques in estimating blast-induced ground vibration in the present study. The ANN model (2-6-8-6-1) was introduced as the most superior model for predicting ground vibration with an RMSE of 0.508, R2 of 0.981 and MAE of 0.405 on the testing dataset. The SVM, CART, and KNN models provided poorer performance with an RMSE of 1.192, 2.820, 1.878; R2 of 0.886, 0.618, 0.737; and MAE of 0.659, 1.631, 0.762, respectively.

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Acknowledgements

This research was supported by Hanoi University of Mining and Geology (HUMG), Hanoi, Vietnam, and Duy Tan University, Da Nang, Vietnam. We also thank the Center for Mining, Electro-Mechanical Research of HUMG.

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Authors and Affiliations

  1. Institute of Research and Development, Duy Tan University, Da Nang 550000, Vietnam

    Hoang Nguyen

  2. Department of Surface Mining, Mining Faculty, Hanoi University of Mining and Geology, 18 Pho Vien, Duc Thang Ward, Bac Tu Liem District, Hanoi, Vietnam

    Xuan-Nam Bui

  3. Center for Mining, Electro-Mechanical Research, Hanoi University of Mining and Geology, 18 Pho Vien, Duc Thang Ward, Bac Tu Liem District, Hanoi, Vietnam

    Xuan-Nam Bui

  4. Department for Management of Science and Technology Development, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Hossein Moayedi

  5. Faculty of Civil Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Hossein Moayedi

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  1. Hoang Nguyen
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Correspondence to Hossein Moayedi.

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Nguyen, H., Bui, XN. & Moayedi, H. A comparison of advanced computational models and experimental techniques in predicting blast-induced ground vibration in open-pit coal mine. Acta Geophys. 67, 1025–1037 (2019). https://doi.org/10.1007/s11600-019-00304-3

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