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Machine Learning Applications: Coal Fire Prediction Using Graham’s Ratio

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Proceedings of the 10th Asian Mining Congress 2023 (AMC 2023)

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Abstract

As the mining industry has evolved, there has been a rise in the number of incidents at mining sites caused by active flames in underground coal mines. It is a complex process that jeopardizes the miner’s life and property. The harm inflicted by fire threats in recent history has drawn the attention of the authorities toward implementing measures that will lessen the risk of natural disasters. It is impossible to exaggerate the significance of this finding in terms of its potential to reduce the risk associated with coal’s ability to self-heal. This study intends to show evidence that machine learning may be successfully utilized to produce accurate forecasts regarding self-healing, and its primary objective is to accomplish this goal. This research led to the development of AdaBoost classification procedures, which were then used to create methods for anticipating the occurrence of spontaneous fires in UG coal mines. The effectiveness of different ML models is compared to one another using quality metric criteria.

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Author information

Authors and Affiliations

  1. Department of Mining Engineering, National Institute of Technology, Rourkela, Odisha, India

    Surendra Kumar Dogra, Jitendra Pramanik & Singam Jayanthu

  2. Department of CSE, Trident Academy of Technology, Bhubaneswar, Odisha, India

    Abhaya Kumar Samal

Authors
  1. Surendra Kumar Dogra
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  2. Jitendra Pramanik
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  3. Singam Jayanthu
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  4. Abhaya Kumar Samal
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Corresponding author

Correspondence to Jitendra Pramanik .

Editor information

Editors and Affiliations

  1. The Mining, Geological and Metallurgical Institute, Kolkata, India

    Amalendu Sinha

  2. The Mining, Geological and Metallurgical Institute, Kolkata, West Bengal, India

    Bhabesh Chandra Sarkar

  3. The Mining, Geological and Metallurgical Institute, Kolkata, West Bengal, India

    Prabhat Kumar Mandal

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Dogra, S.K., Pramanik, J., Jayanthu, S., Samal, A.K. (2023). Machine Learning Applications: Coal Fire Prediction Using Graham’s Ratio. In: Sinha, A., Sarkar, B.C., Mandal, P.K. (eds) Proceedings of the 10th Asian Mining Congress 2023. AMC 2023. Springer Proceedings in Earth and Environmental Sciences. Springer, Cham. https://doi.org/10.1007/978-3-031-46966-4_13

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