Description
Metaheuristic Algorithms in Geotechnical and Geological Engineering
Jahed Armaghani, Danial (Ed. / Hrsg.); Fatahi, Behzad (Ed. / Hrsg.)
ISBN 978-981-92-6292-2 · Springer · VI, 528 p. 158 illus., 135 illus. in color. ·
Description / Beschreibung
This book provides a comprehensive exploration of state-of-the-art technical research and review studies focusing on the use of metaheuristic algorithms in geotechnical and geological engineering. These algorithms are extensively used to address various challenges in the field, such as determining critical slope failure surfaces, improving safety in construction and mining, interpreting geophysical data, identifying subsurface structures and potential hazards, optimizing foundation designs to mitigate earthquake risks, and minimizing environmental issues related to material preparation in both pre-construction planning and post-construction phases. Academics, students, and industry professionals find this book valuable, as it highlights the vital roles of metaheuristic algorithms in enhancing efficiency, longevity, usefulness, and effectiveness in geotechnical and geological problem-solving. Additionally, the chapters in this book have the potential to inspire further interdisciplinary research, particularly in examining the durability and environmental sustainability of current systems.
Contents / Inhaltsverzeichnis
Automated Numerical Analysis for Decision Making and Synthetic Dataset Generation A Case Study on Pipe Assessment Near Excavation.- Innovative Approaches to Predicting the Resilient Modulus of Pavement Subgrade A Focus on Metaheuristic Models.- Enhancing UCS Prediction for Cementitious Grouts in Rock Cable Bolting Systems ANN CatBoost and Metaheuristic Algorithms.- Applications of Metaheuristic Algorithms in Autonomous Construction.- Optimized determination of the rock unconfined compressive strength using metaheuristics algorithms.
Contributors / Mitwirkende
Dr Danial Jahed Armaghani is a Research Fellow in the School of Civil, Environmental and Sociotechnical Engineering at the University of Technology Sydney (UTS), Australia. His research focuses on civil and geotechnical engineering, with interests in slope stability analysis, rock mechanics, tunnelling, surface and deep excavations, and the application of machine learning and optimization techniques to geotechnical problems. Dr. Armaghani has authored more than 400 publications in peer-reviewed journals, books, book chapters and conference proceedings and his publication have been cited more than 32,000 times (Google Scholar). He has been consistently ranked among the top 2% of researchers worldwide (Stanford University Global Citation Ranking) from 2020 to 2025. He is also ranked among the top 0.05% of all scholars worldwide, according to ScholarGPS Highly Ranked Scholars in Engineering and Computer Science.
Professor Behzad Fatahi is Head of the School of Civil, Environmental and Sociotechnical Engineering at the University of Technology Sydney (UTS), Australia, and Professor of Civil and Geotechnical Engineering. His research spans geotechnical engineering, infrastructure resilience, dynamic soil–structure interaction, railway geomechanics, ground improvement, earthquake engineering, and data-driven and machine-learning applications in infrastructure engineering. He has extensive academic and industry experience and has contributed to major infrastructure projects in Australia and internationally. Professor Fatahi has published more than 250 peer-reviewed journal and conference papers and has contributed to books and book chapters in his fields of expertise. He is a Chartered Professional Engineer, Fellow of Engineers Australia, and member of the National Engineering Register, and has supervised more than 20 PhD candidates to successful completion as principal supervisor.
Features / Besonderheiten
Includes a wide range of metaheuristic algorithms in geotechnics for various research purposes Focuses on the utilization of metaheuristic algorithms to address challenges of geotechnical and geological engineering Catalyzes interdisciplinary research with a strong focus on improving the durability and environmental sustainability
