Towards an improved prediction of soil-freezing characteristic curve based on extreme gradient boosting model
作者机构：Department of Civil and Environmental EngineeringThe Hong Kong Polytechnic UniversityHung HomKowloonHong KongChina College of Natural Resources and EnvironmentNorthwest A&F UniversityYangling 712100China Department of Soil ScienceUniversity of ManitobaWinnipegManitobaR3T 2N2 Canada
出 版 物：《Geoscience Frontiers》 (地学前缘（英文版）)
年 卷 期：2024年第15卷第6期
页 面：229-243页
核心收录：
学科分类：09[农学] 0903[农学-农业资源与环境] 090301[农学-土壤学]
基 金：supported by the National Natural Science Foundation of China(Grant No.42177291) Innovation Capability Support Program of Shaanxi Province(2023-JC-JQ-25 and 2021KJXX-11)
主 题：Soil freezing characteristic curve(SFCC) Soil temperature Unfrozen water content XGBoost model Machine Learning Feature importance
摘 要：As an essential property of frozen soils,change of unfrozen water content(UWC)with temperature,namely soil-freezing characteristic curve(SFCC),plays significant roles in numerous physical,hydraulic and mechanical processes in cold regions,including the heat and water transfer within soils and at the land–atmosphere interface,frost heave and thaw settlement,as well as the simulation of coupled thermo-hydro-mechanical *** various models have been proposed to estimate SFCC,their applicability remains limited due to their derivation from specific soil types,soil treatments,and test ***,this study proposes a novel data-driven model to predict the SFCC using an extreme Gradient Boosting(XGBoost)model.A systematic database for SFCC of frozen soils compiled from extensive experimental investigations via various testing methods was utilized to train the XGBoost *** predicted soil freezing characteristic curves(SFCC,UWC as a function of temperature)from the well-trained XGBoost model were compared with original experimental data and three conventional *** results demonstrate the superior performance of the proposed XGBoost model over the traditional models in predicting *** study provides valuable insights for future investigations regarding the SFCC of frozen soils.
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