Pile foundations are structural elements, highly recommended as a load transferring system from shallow inadequate soil layers into competent soil strata with high performance. There are several theoretical and numerical approaches available concerning the pile bearing capacity in cohessionless soil, however, there is a need for the development of an accurate and more robust predictive model. In this technical note, the details of experimental work to investigate the pile bearing capacity penetrated in dense sub rounded sand as confirmed by scanning electronic microscopy (SEM) tests with a Dr of 85% is discussed. A testing programme comprised of three types of model piles (steel open-end, steel closed-end and concrete pile). The piles slend...
This paper presents an artifi cial neural network (ANN) model for the prediction of non-linear behav...
AbstractIn this study, the least square support vector machine (LSSVM) algorithm was applied to pred...
. This paper presents the development of ANN model for prediction of axial capacity of a driven pile...
This study was devoted to examine pile bearing capacity and to provide a reliable model to simulate ...
This investigation aimed to examine the load carrying capacity of model piles embedded in sandy soil...
This study aimed to examine the load carrying capacity of model instrumented piles embedded in sand ...
This investigation aimed to examine the load carrying capacity of piles embedded in sandy soil of va...
The design of pile foundations requires good estimation of the pile load-carrying capacity and settl...
In the last few decades, numerous methods have been developed for predicting the axial capacity of p...
AbstractThe design of pile foundations requires good estimations of the pile load-carrying capacity ...
This paper presents an application of two advanced approaches, Artificial Neural Networks (ANN) and ...
This study was implemented to examine pile load-settlement response and to develop a rapid, highly e...
The design of pile foundations requires good estimation of the pile load-carrying capacity and settl...
Axial bearing capacity (ABC) of piles is usually determined by static load test (SLT). However, cond...
Axial bearing capacity (ABC) of piles is usually determined by static load test (SLT). However, cond...
This paper presents an artifi cial neural network (ANN) model for the prediction of non-linear behav...
AbstractIn this study, the least square support vector machine (LSSVM) algorithm was applied to pred...
. This paper presents the development of ANN model for prediction of axial capacity of a driven pile...
This study was devoted to examine pile bearing capacity and to provide a reliable model to simulate ...
This investigation aimed to examine the load carrying capacity of model piles embedded in sandy soil...
This study aimed to examine the load carrying capacity of model instrumented piles embedded in sand ...
This investigation aimed to examine the load carrying capacity of piles embedded in sandy soil of va...
The design of pile foundations requires good estimation of the pile load-carrying capacity and settl...
In the last few decades, numerous methods have been developed for predicting the axial capacity of p...
AbstractThe design of pile foundations requires good estimations of the pile load-carrying capacity ...
This paper presents an application of two advanced approaches, Artificial Neural Networks (ANN) and ...
This study was implemented to examine pile load-settlement response and to develop a rapid, highly e...
The design of pile foundations requires good estimation of the pile load-carrying capacity and settl...
Axial bearing capacity (ABC) of piles is usually determined by static load test (SLT). However, cond...
Axial bearing capacity (ABC) of piles is usually determined by static load test (SLT). However, cond...
This paper presents an artifi cial neural network (ANN) model for the prediction of non-linear behav...
AbstractIn this study, the least square support vector machine (LSSVM) algorithm was applied to pred...
. This paper presents the development of ANN model for prediction of axial capacity of a driven pile...