An overview of in situ testing and geophysical methods to investigate municipal solid waste landfills. [PDF]
Juarez MB, Mondelli G, Giacheti HL.
europepmc +1 more source
Advancements in predicting soil liquefaction susceptibility: a comprehensive analysis of ensemble and deep learning approaches. [PDF]
Ranjan Kumar D, Wipulanusat W.
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Assessing building damage during station break-out in urban railway construction: real monitoring data. [PDF]
Alajlan ZS +4 more
europepmc +1 more source
Estimation of liquefaction-induced settlement of shallow foundation by machine learning with imbalanced data. [PDF]
Sargin S +4 more
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Real-time prediction of soil bearing capacity in clayey soils using drilling parameters and statistical modeling. [PDF]
Pande P +5 more
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Field investigation of the bearing behavior of grouted gravel pile composite foundations in Karst Terrain. [PDF]
Zhang L, Yan C, Jiang C.
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Pareto-optimized stacked ensemble machine learning framework for predicting bearing capacity of driven piles from static load test data. [PDF]
Abdellatief M, ElNemr A, Altahrany A.
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Liquidity index of the Lublin loess as a function of cone resistance q<sub>c</sub> from CPTU test. [PDF]
Nepelski K +5 more
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Evaluation of Data Acquisition Areas in Geotechnical Seismic Tests: Insights from Field Applications. [PDF]
Kim G.
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Fish Scale-Inspired Flow Control for Corner Vortex Suppression in Compressor Cascades. [PDF]
Shen JL, Yang HC, Yeh SI.
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