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Shear strength estimation of plastic clays with statistical and neural approaches

机译：用统计和神经网络方法估算塑性黏土的抗剪强度

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摘要

Because shear strength parameters highly influence the bearing capacity of soils, several researchers have carried out large number of experimental and theoretical studies aimed at understanding soil strength behaviors. Within this context, the determination of correlations between soil index properties and shear strength parameters for specific soil types is possible. The aim of this study is to observe the performance of statistical and artificial neural network (ANN)-based methods on establishing correlations between index properties and shear strength parameters of normally consolidated plastic clays. To collect modeling data, consolidated-undrained triaxial tests were performed on normally consolidated plastic clays obtained from the same region. Additionally, detailed statistical analyses were conducted on the test data. Results indicate that the ANN-based model is superior in determining the relationships between index properties and shear strength parameters. However, in order to get appropriate outcomes, specific care must be dedicated when applying ANN-based correlation models.
机译：由于抗剪强度参数极大地影响土壤的承载力，因此许多研究人员针对理解土壤强度行为进行了大量的实验和理论研究。在这种情况下，可以确定特定土壤类​​型的土壤指数特性和抗剪强度参数之间的相关性。这项研究的目的是观察基于统计和人工神经网络（ANN）的方法在建立正常固结塑性粘土的指数特性与抗剪强度参数之间的相关性方面的性能。为了收集建模数据，对从同一地区获得的通常固结的塑性粘土进行了固结排水三轴试验。另外，对测试数据进行了详细的统计分析。结果表明，基于ANN的模型在确定指标属性与抗剪强度参数之间的关系方面具有优势。但是，为了获得适当的结果，在应用基于ANN的相关模型时必须特别注意。

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