Novel approach to predicting soil permeability coefficient using Gaussian process regression

Ahmad, Mahmood and Keawsawasvong, Suraparb and Ibrahim, Mohd Rasdan and Waseem, Muhammad and Kashyzadeh, Kazem Reza and Sabri, Mohanad Muayad Sabri (2022) Novel approach to predicting soil permeability coefficient using Gaussian process regression. Sustainability, 14 (14). ISSN 2071-1050, DOI

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In the design stage of construction projects, determining the soil permeability coefficient is one of the most important steps in assessing groundwater, infiltration, runoff, and drainage. In this study, various kernel-function-based Gaussian process regression models were developed to estimate the soil permeability coefficient, based on six input parameters such as liquid limit, plastic limit, clay content, void ratio, natural water content, and specific density. In this study, a total of 84 soil samples data reported in the literature from the detailed design-stage investigations of the Da Nang-Quang Ngai national road project in Vietnam were used for developing and validating the models. The models' performance was evaluated and compared using statistical error indicators such as root mean square error and mean absolute error, as well as the determination coefficient and correlation coefficient. The analysis of performance measures demonstrates that the Gaussian process regression model based on Pearson universal kernel achieved comparatively better and reliable results and, thus, should be encouraged in further research.

Item Type: Article
Funders: Ministry of Science and Higher Education of the Russian Federation (Grant No: 075-15-2021-1333)
Uncontrolled Keywords: Soil permeability coefficient; Gaussian process regression; Pearson universal kernel; Radial basis function; Polynomial
Subjects: G Geography. Anthropology. Recreation > GE Environmental Sciences
T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Engineering > Department of Civil Engineering
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 27 Oct 2023 09:07
Last Modified: 27 Oct 2023 09:07

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