AbstractIn this study, a gene expression programming (GEP) approach was employed to develop modified expressions for predicting the bearing capacity of shallow foundations founded on granular material. The model was validated against the results of load tests on full-scale and model footings obtained from the literature. Two models were developed employing different input variables in the GEP approach. The results achieved using the proposed formulae were compared with those obtained from the Meyerhof and Vesic theories. Statistical analysis was used to demonstrate that the GEP models yielded more accurate results than the traditional solutions
The proposed program for the evaluation of the ultimate bearing capacity of shallow foundations was ...
The settlement design of bored piles socketed into rock has received considerable attention. Althoug...
In most geotechnical problems, it is too difficult to predict the soil and structure behavior accura...
In this study, a gene expression programming (GEP) approach was employed to develop modified express...
AbstractRock masses are commonly used as the underlying layer of important structures such as bridge...
A major concern in design of structures is to provide precise estimations of ultimate bearing capaci...
Gene expression programming has been applied in this work to predict the California bearing ratio (C...
Due to the heterogeneous nature of granular soils and the involvement of many effective parameters i...
An accurate prediction of pile capacity under axial loads is necessary for the design. This paper pr...
The determination of soil compaction parameters, maximum dry density (MDD) and optimum moisture cont...
This study investigates to provide a fast solution to the problem of bearing capacity in layered soi...
The paper contains the analysis 86 field tests and calculations conducted by the authors for predict...
This study examines the potential of the soft computing technique—namely, Gaussian process regressio...
In this study, the employment of the gene expression programming (GEP) technique in forecasting mode...
This paper presents the development of a new model to predict the lateral capacity of piles inserted...
The proposed program for the evaluation of the ultimate bearing capacity of shallow foundations was ...
The settlement design of bored piles socketed into rock has received considerable attention. Althoug...
In most geotechnical problems, it is too difficult to predict the soil and structure behavior accura...
In this study, a gene expression programming (GEP) approach was employed to develop modified express...
AbstractRock masses are commonly used as the underlying layer of important structures such as bridge...
A major concern in design of structures is to provide precise estimations of ultimate bearing capaci...
Gene expression programming has been applied in this work to predict the California bearing ratio (C...
Due to the heterogeneous nature of granular soils and the involvement of many effective parameters i...
An accurate prediction of pile capacity under axial loads is necessary for the design. This paper pr...
The determination of soil compaction parameters, maximum dry density (MDD) and optimum moisture cont...
This study investigates to provide a fast solution to the problem of bearing capacity in layered soi...
The paper contains the analysis 86 field tests and calculations conducted by the authors for predict...
This study examines the potential of the soft computing technique—namely, Gaussian process regressio...
In this study, the employment of the gene expression programming (GEP) technique in forecasting mode...
This paper presents the development of a new model to predict the lateral capacity of piles inserted...
The proposed program for the evaluation of the ultimate bearing capacity of shallow foundations was ...
The settlement design of bored piles socketed into rock has received considerable attention. Althoug...
In most geotechnical problems, it is too difficult to predict the soil and structure behavior accura...