Genetic programming for modelling of geotechnical engineering systems
|dc.contributor.editor||Amir H. Gandomi, Amir H. Alavi and Conor Ryan|
|dc.identifier.citation||Shahin, M. 2015. Genetic programming for modelling of geotechnical engineering systems. In Handbook of Genetic Programming Applications, ed. Amir H. Gandomi, Amir H. Alavi and Conor Ryan, 37-57. Switzerland: Springer.|
Over the last decade or so, artificial intelligence (AI) has proved to provide a high level of competency in solving many geotechnical engineering problems that are beyond the computational capability of classical mathematics and traditional procedures. This chapter presents one of the most interesting AI techniques, i.e. genetic programming (GP), and its applications in geotechnical engineering. In the last few years, GP, which is inspired by natural evolution of the human being, has proved to be successful in modelling several geotechnical engineering problems and has demonstrated superior predictive ability compared to traditional methods. In this chapter, the modelling aspects and formulation of GP are described and explained in some detail and an overview of most successful GP applications in geotechnical engineering are presented and discussed.
|dc.subject||Geotechnical engineering application|
|dc.title||Genetic programming for modelling of geotechnical engineering systems|
|dcterms.source.title||Handbook of Genetic Programming Applications|
|curtin.department||Department of Civil Engineering|
|curtin.accessStatus||Fulltext not available|
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