Spatial prediction of rockhead profile using the Gaussian process regression method

The spatial distribution of rockhead profile has a significant impact on the design and construction of geotechnical engineering structures. Limited by the economic and technical conditions, the borehole data of specific sites are often sparse, which brings great challenges to the accurate predictio...

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Bibliographic Details
Published in:Canadian geotechnical journal 2023-12, Vol.60 (12), p.1849-1860
Main Authors: Deng, Zhi-Ping, Pan, Min, Niu, Jing-Tai, Jiang, Shui-Hua, Wu, Bang-bin, Li, Shuang-long
Format: Article
Language:English
Subjects:
Accuracy
Boreholes
Borings
Construction
Construction sites
Environmental aspects
Gaussian process
Gaussian processes
Geotechnical engineering
Modelling
Predictions
Rock mechanics
Spatial distribution
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Summary:The spatial distribution of rockhead profile has a significant impact on the design and construction of geotechnical engineering structures. Limited by the economic and technical conditions, the borehole data of specific sites are often sparse, which brings great challenges to the accurate prediction of rockhead profile. In this study, a Gaussian process regression (GPR) method is used to predict the rockhead profile. Borehole data from a construction site in Hong Kong are used to evaluate the ability of the GPR method to predict rockhead profile. Besides, the influences of the amount of borehole data on the accuracy of the GPR model and the spatial prediction results of rockhead are investigated. The results indicate that the GPR model based on the square exponential and the Matern covariance function can obtain more accurate prediction results, and the GPR model with limited borehole data can provide a reasonable prediction interval for rockhead depth. With the increase of borehole data, the generalization ability and prediction accuracy of the GPR model gradually improves. In engineering practice, the prediction accuracy and uncertainty degree of the GPR model can be used to judge whether it is necessary to continue to increase borehole data.
ISSN:0008-3674
1208-6010
DOI:10.1139/cgj-2022-0372