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dc.contributor.authorShahin, Mohamed
dc.contributor.editorAmir H. Gandomi, Amir H. Alavi and Conor Ryan
dc.date.accessioned2017-01-30T15:04:54Z
dc.date.available2017-01-30T15:04:54Z
dc.date.created2016-09-22T12:29:03Z
dc.date.issued2015
dc.identifier.citationShahin, 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.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/43111
dc.identifier.doi10.1007/978-3-319-20883-1
dc.description.abstract

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.publisherSpringer
dc.subjectartificial intelligence
dc.subjectGeotechnical engineering application
dc.subjectgenetic programming
dc.subjectmodelling
dc.titleGenetic programming for modelling of geotechnical engineering systems
dc.typeBook Chapter
dcterms.source.startPage37
dcterms.source.endPage57
dcterms.source.titleHandbook of Genetic Programming Applications
dcterms.source.isbn978-3-319-20882-4
dcterms.source.placeSwitzerland
dcterms.source.chapter2
curtin.departmentDepartment of Civil Engineering
curtin.accessStatusFulltext not available


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