@article{Shadi Hanandeh_Saad Farhan Alabdullah_Suha Aldahwi_Ala Obaidat_Hayat Alqaseer_2020, title={DEVELOPMENT OF A CONSTITUTIVE MODEL FOR EVALUATION OF BEARING CAPACITY FROM CPT AND THEORETICAL ANALYSIS USING ANN TECHNIQUES}, volume={19}, url={https://geomatejournal.com/geomate/article/view/1883}, abstractNote={<p>Bearing capacity is significant value in pile design. Various approaches have been introduced <br>to estimate the axial pile capacity. These approaches have restrictions and accordingly did not implement <br>uniform and precise estimation of axial pile capacity. To add a value of the effort to achieve a proper and <br>accurate relationship of a cone penetration test, including axial pile capacity, the Artificial Neural Networks <br>(ANN) method is employed in this paper, which can be applied in cases where the relationship between the <br>input parameters is unknown. In this paper, ANN was used to predict the bearing capacity of bored and driven <br>piles. The present study uses the neural network approach to develop a model that can be adopted to predict <br>bearing capacity values using ANN Techniques and can comfortably accommodate new data as this becomes <br>available. ANN was used to predict the bearing capacity of bored and driven piles. The data, which is used as <br>inputs accompanied by CPT. Furthermore, three artificial neural network models were generated. All models <br>show that ANN provides a more accurate result by comparing it with the available CPT method.</p>}, number={74}, journal={GEOMATE Journal}, author={Shadi Hanandeh and Saad Farhan Alabdullah and Suha Aldahwi and Ala Obaidat and Hayat Alqaseer}, year={2020}, month={Oct.}, pages={229–235} }