Gene-expression programming to predict scour at a bridge abutment

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@Article{Azamathulla:2012a:JH,

• author = "H. Md. Azamathulla",
• title = "Gene-expression programming to predict scour at a bridge abutment",
• journal = "Journal of Hydroinformatics",
• year = "2012",
• volume = "14",
• number = "2",
• pages = "324--331",
• keywords = "genetic algorithms, genetic programming, gene expression programming, artificial neural networks, bridge abutments, local scour, radial basis function",
• ISSN = "1464-7141",
• URL = "http://www.iwaponline.com/jh/014/0324/0140324.pdf",
• DOI = "doi:10.2166/hydro.2011.135",
• size = "8 pages",
• abstract = "The process involved in the local scour at an abutment is so complex that it makes it difficult to establish a general empirical model to provide accurate estimation for scour. This study presents the use of gene-expression programming (GEP), which is an extension of genetic programming (GP), as an alternative approach to estimate the scour depth. The datasets of laboratory measurements were collected from the published literature and used to train the network or evolve the program. The developed network and evolved programs were validated by using the observations that were not involved in training. The proposed GEP approach gives satisfactory results compared with existing predictors and artificial neural network (ANN) modelling in predicting the scour depth at an abutment.",
• notes = "ANN, RBF. 'The overall performance of the GEP model is superior to the ANN model.' p330",

}

Genetic Programming entries for Hazi Mohammad Azamathulla

Citations