Title: Forecasting of slope failures in open cast coal mines using AI and ML algorithms

Authors: Anasuya Ravikanti; Srinivasulu Tadisetty

Addresses: Department of ECE, Kakatiya University, Warangal, Telangana, 506009, India ' Department of ECE, Kakatiya University, Warangal, Telangana, 506009, India

Abstract: Coal is a crucial resource, widely used in industries and power generation. India ranks 3rd in coal production but must import coal to meet growing demand. Coal mining in India is done through underground and open-cast methods. Open-cast mining success depends heavily on the stability of pit slopes, which must remain intact throughout the mine's life. Slope failures in open-cast coal mines pose serious risks to safety, efficiency, and environmental sustainability. This paper presents techniques to predict and forecast such failures using machine learning (ML) and artificial intelligence (AI) algorithms. These innovative models leverage comprehensive datasets, including geological, hydrological, and operational parameters, to improve prediction accuracy. The paper also explores the role of AI in enhancing slope stability in open-cast coal mining, demonstrating how AI and ML algorithms can enhance the reliability of slope failure forecasts.

Keywords: slope failures; coal mining; artificial intelligence; AI; machine learning; ML; prediction; open cast coal mines.

DOI: 10.1504/IJMME.2026.152397

International Journal of Mining and Mineral Engineering, 2026 Vol.17 No.1, pp.19 - 40

Received: 26 Sep 2024
Accepted: 23 Dec 2024
Published online: 18 Mar 2026 *

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