title: Design of jetty piles using artificial neural networks.
abstract: To overcome the complication of jetty pile design process, artificial neural networks (ANN) are adopted. To generate the training samples for training ANN, finite element (FE) analysis was performed 50 times for 50 different design cases. The trained ANN was verified with another FE analysis case and then used as a structural analyzer. The multilayer neural network (MBPNN) with two hidden layers was used for ANN. The framework of MBPNN was defined as the input with the lateral forces on the jetty structure and the type of piles and the output with the stress ratio of the piles. The results from the MBPNN agree well with those from FE analysis. Particularly for more complex modes with hundreds of different design cases, the MBPNN would possibly substitute parametric studies with FE analysis saving design time and cost.
authors.affiliation: Port and Harbor Team, Seoyeong Engineering, Republic of Korea.
authors.forename: Yongjei
authors.identifier: 0000-0002-7986-7277
authors.initials: Y
authors.lastname: Lee
authors.affiliation: Department of Computer Design, School of Engineering and Agriculture, Ulaanbaatar University, Mongolia.
authors.forename: Sungchil
authors.identifier: 0000-0003-4730-6595
authors.initials: S
authors.lastname: Lee
authors.affiliation: Department of Global Environment, School of Environment, Keimyung University, 203 Osan Hall, Dalgubul-Daero, Dalsegu, Daegu 1095, Republic of Korea.
authors.forename: Hun-Kyun
authors.identifier: 0000-0002-8067-4923
authors.initials: HK
authors.lastname: Bae
mesh_terms: D016571:Neural Networks, Computer