• Yeruva Ramana Reddy

The main aim of this study is to explore how artificial intelligence is used in geotechnical engineering in terms of modeling and future forecasts. The geotechnical engineering field focuses on using soils and rocks in engineering structures. In material modeling, soils and rocks naturally display complicated behaviors and a high degree of uncertainty. Over the last three decades, more researchers in the area of geotechnical engineering have created and deployed artificial intelligence (AI) approaches [1]. The effectiveness of these techniques has been attributed to their capacity to forecast intricate nonlinear interactions. Complex geotechnical issues have lately seen an increase in the usage of artificial intelligence (AI) methods. These methods might be due to the inefficiency of the old approaches or the excellent prospects of modern methods to express such complexity [1]. Most fields of geotechnical engineering have used artificial intelligence. Artificial intelligence applications were thoroughly examined and addressed in this study, where they excelled in most of them.

Artificial intelligence, Materials modeling, soil mechanics, artificial neural network, geotechnical engineering, pile foundations, bearing capacity

"Artificial Intelligence in Geotechnical Engineering: Applications, Modeling Aspects, and Future Predictions", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.1, Issue 1, page no.880-883, June-2014, Available :http://www.jetir.org/papers/JETIR1701824.pdf

"Artificial Intelligence in Geotechnical Engineering: Applications, Modeling Aspects, and Future Predictions", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.1, Issue 1, page no. pp880-883, June-2014, Available at : http://www.jetir.org/papers/JETIR1701824.pdf