Pile design is an essential component of geotechnical engineering practice, and pipe piles,
in particular, are increasingly being used for the support of a variety of infrastructure projects …

In this study, comparison between the classical ordinary least square (OLS) regression
technique and the Bayesian conjugate normal linear regression method when the data …

Ridge regression dealswith collinearity in the homoscedastic linear regression model. When
the number of predictors (p) is much larger than the number of observations (n), it gives …

Accurate estimation of the ultimate axial load bearing capacity of piles is necessary to
ensure the safety of the supported structures and to prevent cost overruns. Traditional …

Forecasting RES generation is an important task both in finding the optimal location for
newly commissioned RES generation facilities, and in solving problems of existing electric …

Background: The Cox proportional hazard model has gained ground in Biostatistics and
other related fields. It has been extended to capture different scenarios, part of which are …

The presence of the multicollinearity problem in the predictor data causes the variance of the
ordinary linear regression coefficients to be increased so that the prediction power of the …

Regressions have been continuously received great attention. However, there are still open
issues in regression, and two of the issues is regression with multicollinearity and outlier …

This study proposes a performance comparison between machine learning regression
algorithms and Artificial Neural Network (ANN). The regression algorithms used in this study …

Pile design is an essential component of geotechnical engineering practice, and pipe piles,
in particular, are increasingly being used for the support of a variety of infrastructure projects …