Effect of antecedent conditions on prediction of pore water oressure using artificial neural networks

• Main Authors: Mustafa, Muhammad Raza Ul, Bhuiyan, Rezaur Rahman, Isa, Mohamed Hasnain, Saiedi, Saied, Rahardjo, Harianto
• Other Authors: School of Civil and Environmental Engineering
• Format: Article
• Language: English
• Published: 2014
• Subjects: DRNTU::Engineering::Civil engineering::Geotechnical
• Online Access: https://hdl.handle.net/10356/106288; http://hdl.handle.net/10220/23992; http://dx.doi.org/10.5539/mas.v6n2p6
• Institution: Nanyang Technological University

The effect of antecedent conditions on the prediction of soil pore-water pressure (PWP) using Artificial Neural Network (ANN) was evaluated using a multilayer feed forward (MLFF) type ANN model. The Scaled Conjugate Gradient (SCG) training algorithm was used for training the ANN. Time series data of...