Artificial intelligence design charts for predicting friction capacity of driven pile in clay
Sign Up to like & getrecommendations! Published in 2018 at "Neural Computing and Applications"
DOI: 10.1007/s00521-018-3555-5
Abstract: In this study, five nonlinear prediction tools are used to model and predict the friction capacity of driven piles installed in clay including classical support vector machine (SVM) and two of its variants, namely regularized… read more here.
Keywords: friction; friction capacity; model; clay ... See more keywords
Evolutionary computing to determine the skin friction capacity of piles embedded in clay and evaluation of the available analytical methods
Sign Up to like & getrecommendations! Published in 2020 at "Transportation geotechnics"
DOI: 10.1016/j.trgeo.2020.100372
Abstract: Abstract Deep foundations are very important elements in the routine design of railways and bridges when the loads applied due to these important structures are higher than the bearing capacity of the soil. However, the… read more here.
Keywords: capacity; analytical methods; friction capacity; skin friction ... See more keywords
Effect of edge distance on shear friction capacity of steel plates anchored with reinforcing bars in comparison with headed bolts
Sign Up to like & getrecommendations! Published in 2019 at "Canadian Journal of Civil Engineering"
DOI: 10.1139/cjce-2018-0247
Abstract: The shear friction capacity calculated using clauses 11.6.4 to 11.6.10 in ACI 318-14 or clauses 11.5.1 to 11.5.6 in CSA-A23.3-14 do not take into consideration the effect of edge distance on the shear friction capacity.… read more here.
Keywords: shear friction; edge distance; friction capacity; capacity ... See more keywords
Optimizing the Prediction Accuracy of Friction Capacity of Driven Piles in Cohesive Soil Using a Novel Self-Tuning Least Squares Support Vector Machine
Sign Up to like & getrecommendations! Published in 2018 at "Advances in Civil Engineering"
DOI: 10.1155/2018/6490169
Abstract: This research presents a novel hybrid prediction technique, namely, self-tuning least squares support vector machine (ST-LSSVM), to accurately model the friction capacity of driven piles in cohesive soil. The hybrid approach uses LS-SVM as a… read more here.
Keywords: machine; capacity; friction; friction capacity ... See more keywords