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Estimation Equations for Back Break and Ground Vibration Using Genetic Programming

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Abstract

The advent of advanced computer programs, artificial intelligence techniques, algorithms, and numerical modelling techniques and their application in the mining industry, especially in the blasting field, has increased the efficiency of estimating outcomes (such as Back break and ground vibration). These blasting hazards have led to increased blasting costs and decreased the mine’s operational efficiency. This study has chosen blast design parameters to formulate a back break and ground vibration prediction equation. The formulated equations using Genetic programming used more parameters than those used by empirical equations to estimate ground vibration. The back break and ground vibration equations used significant parameters to estimate the results. The training and validation R2 (coefficient of determination) for ground vibration was 0.8752 and 0.8527, and the back break was 0.8347 and 0.8434, respectively.

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The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

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  1. Department of Mining Engineering, IIT (ISM), Dhanbad, India

    Shankar Kumar, Arvind Kumar Mishra & Bhanwar Singh Choudhary

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  1. Shankar Kumar
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  2. Arvind Kumar Mishra
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  3. Bhanwar Singh Choudhary
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SK: Data Collection, Manuscript writing, Paper Content. AKM & BSC: Discussion on manuscript.

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Correspondence to Shankar Kumar.

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Kumar, S., Mishra, A.K. & Choudhary, B.S. Estimation Equations for Back Break and Ground Vibration Using Genetic Programming. Geotech Geol Eng 41, 3139–3149 (2023). https://doi.org/10.1007/s10706-023-02449-x

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