Abstract
This paper describes the application of the artificial neural network model to predict the lateral load capacity of piles in clay. Three criteria were selected to compare the ANN model with the available empirical models: the best fit line for predicted lateral load capacity ( Q p) and measured lateral load capacity ( Q m), the mean and standard deviation of the ratio Q p/ Q m and the cumulative probability for Q p/ Q m. Different sensitivity analysis to identify the most important input parameters is discussed. A neural interpretation diagram is presented showing the effects of input parameters. A model equation is presented based on neural network parameters.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
