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Blast-induced ground vibration prediction using support vector machine

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Abstract

Ground vibrations induced by blasting are one of the fundamental problems in the mining industry and may cause severe damage to structures and plants nearby. Therefore, a vibration control study plays an important role in the minimization of environmental effects of blasting in mines. In this paper, an attempt has been made to predict the peak particle velocity using support vector machine (SVM) by taking into consideration of maximum charge per delay and distance between blast face to monitoring point. To investigate the suitability of this approach, the predictions by SVM have been compared with conventional vibration predictor equations. Coefficient of determination (CoD) and mean absolute error were taken as a performance measure.

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References

  1. Ambraseys NR, Hendron AJ (1968) Dynamic behaviour of rock masses. Rock mechanics in engineering. Practices, Wiley, London, pp 203–207

    Google Scholar 

  2. Bureau of Indian Standard (1973) Criteria for safety and design of structures subjected to underground blast. ISI Bulletin, IS-6922

  3. Cristianini N, Shawe-Taylor NJ (2000) An introduction to support vector machines. Cambridge University Press, Cambridge

    Google Scholar 

  4. Duvall WI, Fogleson DE (1962) Review of criteria for estimating damage to residences from blasting vibration, USBM-I, 5968

  5. Duvall WI, Petkof B (1959) Spherical propagation of explosion of generated strain pulses in rocks, USBM, RI 5483, pp 21–22

  6. Feng XT, Zhao H, Li S (2004) Modeling non-linear displacement time series of geo-materials using evolutionary support vector machines. Int J Rock Mech Min Sci 41(7):1087–1107

    Article  Google Scholar 

  7. ISRM (1992) Suggested method for blast vibration monitoring. Int J Rock Mech Min Sci and Geomech Abstr 29:145–146

    Google Scholar 

  8. John CP (1998) Sequential minimal optimization: a fast algorithm for training support vector machines. Technical report, MSR-TR-98-14

  9. Khandelwal M, Singh TN (2006) Prediction of blast induced ground vibrations and frequency in opencast mine—a neural network approach. J Sound Vib 289:711–725

    Article  Google Scholar 

  10. Khandelwal M, Singh TN (2007) Evaluation of blast induced ground vibration predictors. Soil Dyn Earthq Eng 27:116–125

    Article  Google Scholar 

  11. Khandelwal M, Singh TN (2009) Prediction of blast induced ground vibration using artificial neural network. Int J Rock Mech Min Sci 46:1214–1222

    Article  Google Scholar 

  12. Khandelwal M (2010) Evaluation and prediction of blast induced ground vibration using support vector machine. Int J Rock Mech Min Sci 47(3):509–516

    Article  Google Scholar 

  13. Langefors U, Kihlstrom B (1963) The modern technique of rock blasting. Wiley, New York

    Google Scholar 

  14. Liu KY, Qiao CS, Tian SF (2004) Design of tunnel shotcrete-bolting support based on a support vector machine approach. Int J Rock Mech Min Sci 41(3):510–511

    Article  Google Scholar 

  15. Muller KR, Smola JA, Scholkopf B (1997) Prediction time series with support vector machines. In: Proceedings of international conference on artificial neural networks, Switzerland, Lausanne, pp 999–1004

  16. Pal Roy P (1993) Putting ground vibration predictors into practice. Colliery Guardian 241:63–67

    Google Scholar 

  17. Schmidt M (1996) Identifying speaker with support vector networks. In: Interface ‘96 Proceedings, Sydney

  18. Scholkopf B, Burges C, Vapnik V (1995) Extracting support data for a given task. In: Proceedings of the first international conference on knowledge discovery and data mining. AAAI Press, Menlo Park

  19. Siskind DE, Stagg MS, Kopp JW, Dowding CH (1980) Structure response and damage produced by ground vibration from surface mine blasting. US Bureau of Mines, RI, 8507, p 74

  20. Vapnik VN (1998) Statistical learning theory. Wiley, New York

    MATH  Google Scholar 

  21. Witten IH, Frank E (2005) Data mining: practical machine learning tools and techniques, 2nd edn. Morgan Kaufmann, San Francisco

    Google Scholar 

Download references

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Authors and Affiliations

  1. Department of Mining Engineering, College of Technology and Engineering, Maharana Pratap University of Agriculture and Technology, Udaipur, 313 001, India

    Manoj Khandelwal

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  1. Manoj Khandelwal
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Correspondence to Manoj Khandelwal.

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Khandelwal, M. Blast-induced ground vibration prediction using support vector machine. Engineering with Computers 27, 193–200 (2011). https://doi.org/10.1007/s00366-010-0190-x

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  • DOI: https://doi.org/10.1007/s00366-010-0190-x

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