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Introduction and Applications of Machine Learning in Geotechnics

Introduction and Applications of Machine Learning in Geotechnics - Paperback

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Availability:In StockContributor:Zong Woo Geem, Sinan Melih NigdeliPublish date:4/20/2026Pages:388
Languages:EnglishPublisher:ElsevierISBN-13:9780443414817ISBN-10:0443414815UPC:9780443414817Book Category:Science, ComputersBook Subcategory:Earth Sciences, Business & Productivity SoftwareBook Topic:Geology, Business IntelligenceSize:9.07 x 5.99 x 0.80 inchesWeight:0.676Product ID:SCX2BVV7V8
Introduction and Applications of Machine Learning in Geotechnics offers a comprehensive exploration of machine learning methodologies and their diverse applications in geotechnical engineering. The book begins with a detailed review of machine learning methods tailored for geotechnical applications, setting the foundation for subsequent chapters. Regression models are utilized to predict shear wave velocities while optimization-based approaches are employed to determine the optimal dimensions of reinforced concrete (RC) retaining walls. The book further explores the identification of gravelly soil through optimized machine learning models and predicts stress-strain responses using data from simple shear tests.

Additionally, it outlines the forecasting of liquefaction events triggered by seismic activities and estimates the uniaxial compressive strength of soil using machine learning techniques. The prediction of vertical effective stress and specific penetration resistance is examined to enhance soil characterization and geotechnical analyses. The book's authors provide valuable insights for geotechnical engineers and researchers seeking to leverage advanced computational tools for enhanced geotechnical assessments and design processes.

Languages:EnglishPublisher:ElsevierISBN-13:9780443414817ISBN-10:0443414815UPC:9780443414817Book Category:Science, ComputersBook Subcategory:Earth Sciences, Business & Productivity SoftwareBook Topic:Geology, Business IntelligenceSize:9.07 x 5.99 x 0.80 inchesWeight:0.676Product ID:SCX2BVV7V8
Geem, Zong Woo: - "

Prof. Zong Woo Geem works for the Department of Smart City at Gachon University in South Korea. He has obtained B.Eng. from Chung-Ang University, M.Eng. and Ph.D. from Korea University, and M.Sc. from Johns Hopkins University, and researched at Virginia Tech, University of Maryland - College Park, and Johns Hopkins University. He invented a music-inspired optimization algorithm, Harmony Search (HS), which has been applied to various scientific and engineering problems as well as social and cultural problems. His research interest includes theoretical background (e.g. novel human-experience-based derivative of HS rather than existing analytic-calculus-based derivative) and problem-specific development (e.g. problem-specific operator of HS) of phenomenon-mimicking algorithm and its applications to sustainability & culture issues.

"Bekdaş, Gebrail: - "

Gebrail Bekdaş, Professor, is researcher in Mechanics at Istanbul University - Cerrahpaşa. He obtained his DPhil in Structural Engineering from Istanbul University with a thesis subject of design of cylindrical walls. He was one of the guest editors in 2017 special issue of KSCE Journal of Civil Engineering. He co-chaired 6th International Conference on Harmony Search, Soft Computing and Applications (ICHSA 2020). He has authored about 500 papers for journals and scientific events.

"Nigdeli, Sinan Melih: - "

Sinan Melih Nigdeli, Professor, is researcher in Mechanics at Istanbul University - Cerrahpaşa. He obtained his DPhil in Structural Engineering from Istanbul Technical University with a thesis subject of active control. He was one of the guest editors in 2017 special issue of KSCE Journal of Civil Engineering. He co-chaired 6th International Conference on Harmony Search, Soft Computing and Applications (ICHSA 2020). He has authored about 500 papers for journals and scientific events.

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Publisher: Elsevier

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