Articles | Volume 382
https://doi.org/10.5194/piahs-382-443-2020
https://doi.org/10.5194/piahs-382-443-2020
Pre-conference publication
 | 
22 Apr 2020
Pre-conference publication |  | 22 Apr 2020

Parameterisation of the Koppejan settlement prediction model using cone penetration testing and gradient boosting

Kevin Duffy, Klaas Siderius, and Mike Long

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Short summary
This study examines how field tests can be used to accurately assess the compressibility of soils across the Netherlands and to improve on the significant margin of error shown in settlement calculations. It was found that there is potential in using machine learning methods to obtain a relationship between field test results and compressibility parameters, reducing the influence of human errors and misinterpretation on the prediction of settlement.