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Outputs (4)

Prediction of strength enhancement of subgrade soil reinforced with geotextile using artificial neural network and M5P model tree (2020)
Journal Article

Geosynthetics layers are being implemented as reinforcement to enhance the strength of subgrade soil (which is calculated in terms of CBR). Present research work, aims at investigating the strength enhancement in terms of CBR through experimental stu... Read More about Prediction of strength enhancement of subgrade soil reinforced with geotextile using artificial neural network and M5P model tree.

Modeling oblique load carrying capacity of batter pile groups using neural network, random forest regression and M5 model tree (2018)
Journal Article

M5 model tree, random forest regression (RF) and neural network (NN) based modelling approaches were used to predict oblique load carrying capacity of batter pile groups using 247 laboratory experiments with smooth and rough pile groups. Pile length... Read More about Modeling oblique load carrying capacity of batter pile groups using neural network, random forest regression and M5 model tree.

Modeling of oblique load test on batter pile group based on support vector machines and gaussian regression (2017)
Journal Article

This paper evaluates the potential of two machine learning approaches i.e. Support vector machine (SVR) and Gaussian processes (GP) regression to model the oblique load capacity of batter pile groups. Linear regression was used to compare the perform... Read More about Modeling of oblique load test on batter pile group based on support vector machines and gaussian regression.