Integrating AI with seismic soil-structure interaction: From foundations to underground structures

This paper reviews the current literature on the use of artificial intelligence in soil structure interaction (SSI) analysis and design. This paper provides a comprehensive review synthesizing current AI applications across multiple SSI domains, balancing breadth of coverage with analytical depth in each subdomain. These include some of the significant features of the review such as the foundation engineering, underground structures and seismic SSI. Some approaches such as artificial neural networks, support vector machines, genetic programming and Bayesian methods are briefly described with respect to the SSI application area. The applicability of these techniques, their shortcomings and modern trends are viewed critically. The paper presents an overview and discussion of various articles in the field of AI for SSI over the last decade. Based on the analysis, some of the major issues that may be encountered in applying AI for SSI problems are discussed as well as possible future research avenues are pointed out. The present review will thus provide the readers a single source of information compiling the state-of-the-art advances in using AI in soil-structure interaction.