Artificial Intelligence and Soft Computing in Deep Exploration: A Review of Applications and Impacts

This research reviews artificial intelligence in deep exploration together with soft computing, outlining applications and impacts both techniques have on a wide array of sectors. The integration of AI procedures like machine learning and neural networks together with soft computing approaches such as fuzzy logic and genetic algorithms has dramatically modernized the processes for data analysis and decision-making. These technologies have been allowing the interpretation of big data in geotechnical explorations and allowed one to predict at locations with a high degree of accuracy. AI-driven simulations amplify operational efficiencies in the environments that are also unreachable or hard to analyze traditionally. Some case studies presented were projects having ensured better results in mineral explorations, optimization of drilling of oil, and in environmental monitoring. It also deliberates on the ethical considerations and probable socio-economic impacts of deploying these advanced technologies in deep exploration settings. This paper synthesizes current trends and future directions, hence providing valuable insights for researchers and practitioners who aim at leveraging AI and soft computing for sustainable resource management.

Artificial Intelligence and Soft Computing in Deep Exploration: A Review of Applications and Impacts Keywords:

Deep exploration , artificial intelligence , Soft Computing , advanced algorithms , mining industry