Prediction of blast-induced air overpressure using support vector machine View Full Text


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Article Info

DATE

2009-10-07

AUTHORS

Manoj Khandelwal, P. K. Kankar

ABSTRACT

Prediction of blast-induced air overpressure (AOP) is very complicated and intricate due to the number of influencing parameters affecting air wave propagation. In this paper, an attempt has been made to predict the blast-induced AOP by support vector machine (SVM) using maximum charge per delay and distance from blast-face to monitoring station of AOP. To investigate the suitability of this approach, SVM predictions are compared with a generalized predictor equation. Seventy-five air blasts were monitored at different locations around three mines. AOP data sets of two limestone mines are taken for the training and testing of the SVM network as well as to determine site constants for generalized equation. The remaining mine data sets are used for the validation and comparison of AOP. More... »

PAGES

427-433

References to SciGraph publications

  • 1997. Predicting time series with support vector machines in ARTIFICIAL NEURAL NETWORKS — ICANN'97
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s12517-009-0092-7

    DOI

    http://dx.doi.org/10.1007/s12517-009-0092-7

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