Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Machine Learning for Data-Centric Geotechnics

Machine Learning for Data-Centric Geotechnics

Phoon, Kok-Kwang
Tang, Chong
Cao, Zi-Jun

Hardcover

Series: Challenges in Geotechnical and Rock Engineering

Technology & EngineeringGeneral Computers

ISBN10: 1032886544
ISBN13: 9781032886541
Publisher: CRC Press
Published: Aug 25 2026
Pages: 472
Weight: 2.37
Height: 1.06 Width: 7.00 Depth: 10.00
Language: English

Machine learning and other digital technologies fed with large datasets offer a major set of tools for practical geotechnical design. Large language models and other generative AIs can perform cognitive tasks currently undertaken by humans -- and might even predict the next event based on some time series. This depends on a balance of data centricity, fit-for (and transform) practice, and geotechnical context, and can be achieved by the integration of information, data, techniques, tools, perspectives, concepts, theories, along with experience from both geotechnical engineering and machine learning in computer science. And yet good engineering and research outcomes are still dependent on how practice (which includes the workforce) is improved or even transformed in the longer term to better serve end-users. This collection of focused chapters from a group of specialists presents principles and broad up to date practice of machine learning, along with a number of example areas of site characterization, design and construction in geotechnics.

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