Genetic programming for modelling of geotechnical engineering systems
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 interest...
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| Format: | Book Chapter |
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Springer
2015
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| Online Access: | http://hdl.handle.net/20.500.11937/43111 |
| _version_ | 1848756600905400320 |
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| author | Shahin, Mohamed |
| author2 | Amir H. Gandomi |
| author_facet | Amir H. Gandomi Shahin, Mohamed |
| author_sort | Shahin, Mohamed |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T09:14:47Z |
| format | Book Chapter |
| id | curtin-20.500.11937-43111 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:14:47Z |
| publishDate | 2015 |
| publisher | Springer |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-431112023-02-27T07:34:28Z Genetic programming for modelling of geotechnical engineering systems Shahin, Mohamed Amir H. Gandomi Amir H. Alavi Conor Ryan artificial intelligence Geotechnical engineering application genetic programming modelling 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. 2015 Book Chapter http://hdl.handle.net/20.500.11937/43111 10.1007/978-3-319-20883-1 Springer restricted |
| spellingShingle | artificial intelligence Geotechnical engineering application genetic programming modelling Shahin, Mohamed Genetic programming for modelling of geotechnical engineering systems |
| title | Genetic programming for modelling of geotechnical engineering systems |
| title_full | Genetic programming for modelling of geotechnical engineering systems |
| title_fullStr | Genetic programming for modelling of geotechnical engineering systems |
| title_full_unstemmed | Genetic programming for modelling of geotechnical engineering systems |
| title_short | Genetic programming for modelling of geotechnical engineering systems |
| title_sort | genetic programming for modelling of geotechnical engineering systems |
| topic | artificial intelligence Geotechnical engineering application genetic programming modelling |
| url | http://hdl.handle.net/20.500.11937/43111 |