About this Research Topic
Welcome to this Research Topic dedicated to the "Advancement of Artificial Intelligence in Geotechnical Engineering." Over the past few decades, the field of geotechnical engineering has witnessed significant advancements, propelled by technological innovations and interdisciplinary collaborations. Among these innovations, artificial intelligence (AI) has emerged as a transformative force, revolutionizing the way we approach challenges in soil mechanics, foundation engineering, slope stability analysis, and geotechnical site characterization.
This Research Topic aims to showcase the latest research, methodologies, and applications at the intersection of AI and geotechnical engineering. By harnessing the power of AI techniques such as machine learning, deep learning, evolutionary algorithms, and data analytics, researchers and practitioners have been able to address complex geotechnical problems with unprecedented accuracy, efficiency, and reliability.
The papers presented in this special issue cover a wide spectrum of topics, including but not limited to:
• Predictive Modeling: Utilizing AI algorithms to develop predictive models for soil behavior, settlement analysis, and geotechnical parameter estimation.
• Site Characterization: Leveraging AI techniques for automated interpretation of geotechnical data from site investigations, including soil properties, stratigraphy, and ground conditions.
• Risk Assessment: Applying AI-driven approaches to assess and mitigate risks associated with geotechnical hazards such as landslides, liquefaction, and ground subsidence.
• Optimization and Design: Integrating AI algorithms into the design process for optimizing geotechnical structures, foundations, and earthworks.
• Decision Support Systems: Developing AI-based decision support systems to aid geotechnical engineers in project planning, management, and decision-making.
Through this collection of articles, we aim to foster dialogue and collaboration among researchers, engineers, and industry professionals working at the forefront of AI and geotechnical engineering. By sharing insights, methodologies, and best practices, we endeavor to accelerate the adoption of AI technologies in geotechnical practice, ultimately enhancing the resilience, sustainability, and safety of civil infrastructure worldwide.
We extend our gratitude to all the authors, reviewers, and contributors who have made this Research Topic possible. We hope that the diverse perspectives and innovative approaches presented herein will inspire future research and advancements in this exciting field.
This Research Topic aims to showcase the latest research, methodologies, and applications at the intersection of AI and geotechnical engineering. By harnessing the power of AI techniques such as machine learning, deep learning, evolutionary algorithms, and data analytics, researchers and practitioners have been able to address complex geotechnical problems with unprecedented accuracy, efficiency, and reliability.
The papers presented in this special issue cover a wide spectrum of topics, including but not limited to:
• Predictive Modeling: Utilizing AI algorithms to develop predictive models for soil behavior, settlement analysis, and geotechnical parameter estimation.
• Site Characterization: Leveraging AI techniques for automated interpretation of geotechnical data from site investigations, including soil properties, stratigraphy, and ground conditions.
• Risk Assessment: Applying AI-driven approaches to assess and mitigate risks associated with geotechnical hazards such as landslides, liquefaction, and ground subsidence.
• Optimization and Design: Integrating AI algorithms into the design process for optimizing geotechnical structures, foundations, and earthworks.
• Decision Support Systems: Developing AI-based decision support systems to aid geotechnical engineers in project planning, management, and decision-making.
Through this collection of articles, we aim to foster dialogue and collaboration among researchers, engineers, and industry professionals working at the forefront of AI and geotechnical engineering. By sharing insights, methodologies, and best practices, we endeavor to accelerate the adoption of AI technologies in geotechnical practice, ultimately enhancing the resilience, sustainability, and safety of civil infrastructure worldwide.
We extend our gratitude to all the authors, reviewers, and contributors who have made this Research Topic possible. We hope that the diverse perspectives and innovative approaches presented herein will inspire future research and advancements in this exciting field.
Keywords: to be confirmed
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
