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Novel Hybrid X GBoost Model to Forecast soil shear strength Based on Some soil Index Tests

Computer Modeling in Engineering & Sciences 2023年第9期136卷 2527-2550页

作者： Ehsan Momeni Biao He Yasin Abdi Danial Jahed Armaghani Department of Civil Engineering Faculty of EngineeringLorestan UniversityKhorramabad***Iran Department of Civil Engineering Faculty of EngineeringUniversiti MalayaKuala Lumpur50603Malaysia Department of Geology Faculty of SciencesLorestan UniversityKhorramabad***Iran Department of Urban Planning Engineering Networks and SystemsInstitute of Architecture and ConstructionSouth Ural State UniversityChelyabinsk454080Russia

When building geotechnical constructions like retaining walls and dams is of interest,one of the most important factors to consider is the soil’s shear strength *** study makes an effort to propose a novel predictive model of shear *** study implements an extreme gradient boosting(XGBoost)technique coupled with a powerful optimization algorithm,the salp swarm algorithm(SSA),to predict the shear strength of various *** do this,a database consisting of 152 sets of data is prepared where the shear strength(τ)of the soil is considered as the model output and some soil index tests(e.g.,dry unit weight,water content,and plasticity index)are set as model *** is designed and tuned using both effective parameters of XGBoost and SSA,and themost accuratemodel is introduced in this *** theSSA-XGBoostmodel is assessedbased on the coefficient of determination(R2)and variance account for(VAF).Overall,the obtained values of R^(2) and VAF(0.977 and 0.849)and(97.714%and 84.936%)for training and testing sets,respectively,confirm the workability of the developed model in forecasting the soil shear *** investigate the model generalization,the prediction performance of the model is tested for another 30 sets of data(validation data).The validation results(e.g.,R^(2) of 0.805)suggest the workability of the proposed ***,findings suggest that when the shear strength of the soil cannot be determined directly,the proposed hybrid XGBoost-SSA model can be utilized to assess this parameter.

关键词： Predictive model salp swarm algorithm soil index tests soil shear strength XGBoost

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soil shear strength: AN INDICATOR FOR ERODIBILITY OF THE LOESS soilS

引用

International Journal of Sediment Research 1994年第1期 77-91页

作者： WANG Guiping WEI Zhongping and ZHANG Zhiguo

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ＳＯＩＬＳＨＥＡＲＳＴＲＥＮＧＴＨ：ＡＮＩＮＤＩＣＡＴＯＲＦＯＲＥＲＯＤＩＢＩＬＩＴＹＯＦＴＨＥＬＯＥＳＳＳＯＩＬＳＷＡＮＧＧｕｉｐｉｎｇ；ＷＥＩＺｈｏｎｇｐｉｎｇａｎｄＺＨＡＮＧＺｈｉｇｕｏＡｂｓｔｒａｃｔ：ＦｉｅｌｄｅｘｐｅｒｉｍｅｎｔＳｕｎｄｅ...

关键词： soil shear strength interrill erosion rill initiation and erosion loess soils

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