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首页> 外文期刊>Acta Geotechnica Slovenica >PREDICTION OF THE COMPACTION PARAMETERS FOR COARSE-GRAINED SOILS WITH FINES CONTENT BY MLR AND GEP
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PREDICTION OF THE COMPACTION PARAMETERS FOR COARSE-GRAINED SOILS WITH FINES CONTENT BY MLR AND GEP

机译:用MLR和GEP预测含细颗粒粗粒土的压实参数

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摘要

The determination of the compaction parameters of soils,the maximum dry unit weight (γdmax) and the optimum water content (wopt), at various compaction energy (E)levels is an important process. The aim of this study is to develop correlations in order to estimate the compaction parameters dependent on the compaction energy for coarse-grained soils with various fines contents on which limited studies exist in the literature. Genetic Expression Programming (GEP) and Multi Linear Regression (MLR) analyses are used in the derivation of the correlations for the prediction of γdmax and wopt obtained from Standard Proctor (SP) and Modified Proctor (MP) tests with the index properties of coarse-grained soils with various fines contents. To develop the models, a total of 86 data sets collected from university laboratories in Turkey and six parameters, such as gravel content (G %), sand content (S %), fines content (FC %), liquid limit (wL %) and plasticity index (IP %) of fines content and compaction energy (E Joule), are used. The performance of the models is comprehensively examined using several statistical verification tools. The results revealed that the GEP and MLR models are fairly promising approaches for the prediction of the maximum dry unit weight and the optimum water content of cohesionless soils with various fines contents at SP and MP compaction energy levels. The proposed correlations are reasonable ways to estimate the compaction parameters for the preliminary design of a project where there are financial and time limitations.
机译:确定不同压实能量(E)水平下土壤的压实参数,最大干重(γdmax)和最佳含水量(wopt)是重要的过程。这项研究的目的是发展相关性,以估计依赖于压实能量的具有各种细粉含量的粗粒土的压实参数,文献中对此进行了有限的研究。遗传表达式编程(GEP)和多元线性回归(MLR)分析用于推导相关性,以预测从标准Proctor(SP)和修正Proctor(MP)测试获得的γdmax和wopt的指标特性。细粒含量不同的粒状土壤。为了开发模型,总共从土耳其的大学实验室收集了86个数据集和六个参数,例如砾石含量(G%),沙子含量(S%),细粉含量(FC%),液体极限(wL%)使用细粉含量和压实能(E焦耳)的可塑性指数(IP%)。使用几种统计验证工具全面检查了模型的性能。结果表明,GEP和MLR模型是预测SP和MP压实能级下各种细度含量的无粘性土壤最大干重和最佳含水量的有前途的方法。所提出的相关性是估算有财务和时间限制的项目的初步设计的压实参数的合理方法。

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