Dorthi, K.Kumar, A.Ram Chandar, K.R.2026-02-062022Lecture Notes in Electrical Engineering, 2022, Vol.862, , p. 573-58218761100https://doi.org/10.1007/978-981-19-0252-9_52https://idr.nitk.ac.in/handle/123456789/29958Numerical modeling simulation has found to be best solution for predicting slope and partition stability over old underground coal workings. But it has taken huge time to complete a single simulation model. In this regard, machine learning-based framework is used to predict the stability of old galleries. A case study is taken up in opencast mine and simulation is carried out using numerical model and machine learning-based framework. Framework has shown an overall accuracy of 94–95% for different slope and partition stability. Framework shows a speedup of 2366 × against numerical simulator. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.Machine learningNumerical modelingOpencast minePartitionSlopeSupport vector regression