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Developing a least squares support vector machine for estimating the blast-induced flyrock

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Abstract

In blasting operations, the main purpose is to provide appropriate rock fragmentation and to avoid adverse effects such as flyrock and vibration. This paper presents the applicability of least squares support vector machines (LS-SVM) for estimating the blast-induced flyrock. For comparison aim, support vector regression (SVR) was also employed. The case study was carried out in the Gole-E-Gohar iron mine of Iran in which the values of burden to spacing ratio, hole length to burden ratio, subdrilling, stemming, charge per delay, rock density and powder factor were measured for 90 blasting operations. The mentioned seven parameters were used as the independent or input parameters in modeling, while, the values of flyrock distance were assigned as the models output. To train the models, 72 datasets were adopted and then the remaining 18 datasets were adopted to test the models. The models performance was compared by several statistical criteria such as R square (R 2) and mean square error (MSE). According to obtained results, the LS-SVM with the R 2 of 0.969 and MSE of 16.25 can prove more useful than the SVR with the R 2 of 0.945 and MSE of 31.58 in estimation of blast-induced flyrock. At the end, sensitivity analysis was also performed and according to the results, powder factor and rock density were the most effective parameters on the flyrock in this case study.

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Acknowledgements

The authors thank the technical team and personnel of Gol-E-Gohar iron mine for their helps in gathering of data for this work. The authors are also interested to express his genuine gratitude to other persons who kindly gave us their worthy advises in the paper preparation.

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Authors and Affiliations

  1. Young Researchers and Elite Club, Mashhad Branch, Islamic Azad University, Mashhad, Iran

    Hima Nikafshan Rad

  2. Young Researchers and Elite Club, Qom Branch, Islamic Azad University, Qom, Iran

    Mahdi Hasanipanah

  3. Department of Mining Engineering, Faculty of Engineering, University of Kurdistan, Sanandaj, Iran

    Mohammad Rezaei

  4. Department of Civil Engineering, Payame Noor University (PNU), 19395-4697, Tehran, Iran

    Amin Lotfi Eghlim

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  1. Hima Nikafshan Rad
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  2. Mahdi Hasanipanah
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  3. Mohammad Rezaei
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  4. Amin Lotfi Eghlim
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Correspondence to Mohammad Rezaei.

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Rad, H.N., Hasanipanah, M., Rezaei, M. et al. Developing a least squares support vector machine for estimating the blast-induced flyrock. Engineering with Computers 34, 709–717 (2018). https://doi.org/10.1007/s00366-017-0568-0

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  • DOI: https://doi.org/10.1007/s00366-017-0568-0

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