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Estimation of air-overpressure produced by blasting operation through a neuro-genetic technique

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Abstract

Blasting operations usually produce significant environmental problems which may cause severe damage to the nearby areas. Air-overpressure (AOp) is one of the most important environmental impacts of blasting operations which needs to be predicted and subsequently controlled to minimize the potential risk of damage. In order to solve AOp problem in Hulu Langat granite quarry site, Malaysia, three non-linear methods namely empirical, artificial neural network (ANN) and a hybrid model of genetic algorithm (GA)–ANN were developed in this study. To do this, 76 blasting operations were investigated and relevant blasting parameters were measured in the site. The most influential parameters on AOp namely maximum charge per delay and the distance from the blast-face were considered as model inputs or predictors. Using the five randomly selected datasets and considering the modeling procedure of each method, 15 models were constructed for all predictive techniques. Several performance indices including coefficient of determination (R 2), root mean square error and variance account for were utilized to check the performance capacity of the predictive methods. Considering these performance indices and using simple ranking method, the best models for AOp prediction were selected. It was found that the GA–ANN technique can provide higher performance capacity in predicting AOp compared to other predictive methods. This is due to the fact that the GA–ANN model can optimize the weights and biases of the network connection for training by ANN. In this study, GA–ANN is introduced as superior model for solving AOp problem in Hulu Langat site.

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Acknowledgments

The authors would like to extend their appreciation to the Government of Malaysia and Universiti Teknologi Malaysia for the FRGS Grant No. 4F406 and for providing the required facilities that made this research possible. Also, the authors are grateful to the reviewers for their constructive comments.

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Authors and Affiliations

  1. Department of Geotechnics and Transportation, Faculty of Civil Engineering, Universiti Teknologi Malaysia (UTM), 81310, Skudai, Johor, Malaysia

    Edy Tonnizam Mohamad, Danial Jahed Armaghani, Bhatawdekar Ramesh Murlidhar & Mohd Nur Asmawisham Alel

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

    Mahdi Hasanipanah

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  1. Edy Tonnizam Mohamad
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  2. Danial Jahed Armaghani
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Correspondence to Danial Jahed Armaghani.

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Tonnizam Mohamad, E., Jahed Armaghani, D., Hasanipanah, M. et al. Estimation of air-overpressure produced by blasting operation through a neuro-genetic technique. Environ Earth Sci 75, 174 (2016). https://doi.org/10.1007/s12665-015-4983-5

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