Paper Key : IRJ************453
Author: Sobuj Hasan, Sadman Bin Shafiq, Lubna Khatun
Date Published: 17 Nov 2023
Abstract
Mineral exploration is a complex and challenging process, requiring vast amounts of data to be analyzed tomake informed decisions. Traditional methods of mineral exploration are time-consuming, expensive, and oftenyield low success rates. However, the emergence of Artificial Intelligence (AI) and Machine Learning (ML)presents an opportunity to revolutionize the mining industry. This review article investigates the current state-of-the-art applications of AI and ML in mineral exploration, evaluates their effectiveness and limitations, andidentifies the potential benefits and challenges of their adoption. The study highlights that AI and MLtechniques can significantly increase the efficiency and success rate of mining projects. Various AI and MLalgorithms such as Neural Networks, Decision Trees, and Random Forests are being used for mineralexploration. These techniques help in identifying patterns and correlations in the vast amount of data, reducingthe time and cost involved in mineral exploration. The study also identifies potential limitations such as theneed for high-quality data, the lack of interpretability of the results, and the ethical considerations that need tobe addressed when using AI and ML in mining. The findings of this study have significant implications for themining industry. The adoption of AI and ML techniques in mineral exploration can lead to increasedprofitability, reduced costs, and improved environmental and social impacts. The study providesrecommendations for future research and development of AI and ML techniques in mineral exploration. Inconclusion, the potential of AI and ML in mineral exploration is immense, and their adoption could lead to aparadigm shift in the mining industry.
DOI LINK : 10.56726/IRJMETS45281 https://www.doi.org/10.56726/IRJMETS45281