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A platform for research: civil engineering, architecture and urbanism
Undrained lateral load capacity of piles in clay using artificial neural network
AbstractThis 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 (Qp) and measured lateral load capacity (Qm), the mean and standard deviation of the ratio Qp/Qm and the cumulative probability for Qp/Qm. 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.
Undrained lateral load capacity of piles in clay using artificial neural network
AbstractThis 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 (Qp) and measured lateral load capacity (Qm), the mean and standard deviation of the ratio Qp/Qm and the cumulative probability for Qp/Qm. 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.
Undrained lateral load capacity of piles in clay using artificial neural network
Das, Sarat Kumar (author) / Basudhar, Prabir Kumar (author)
Computers and Geotechnics ; 33 ; 454-459
2006-08-24
6 pages
Article (Journal)
Electronic Resource
English
Undrained lateral load capacity of piles in clay using artificial neural network
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