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dc.contributor.authorShahin, Mohamed
dc.identifier.citationShahin, M. 2015. Use of evolutionary computing for modelling some complex problems in geotechnical engineering. Geomechanics & Geoengineering: An International Journal. 10 (2): pp. 109-125.

In this paper, the feasibility of using evolutionary computing for solving some complex problems in geotechnical engineering is investigated. The paper presents a relatively new technique, i.e. evolutionary polynomial regression (EPR), for modelling three practical applications in geotechnical engineering including the settlement of shallow foundations on cohesionless soils, pullout capacity of small ground anchors and ultimate bearing capacity of pile foundations. The prediction results from the proposed EPR models are compared with those obtained from artificial neural network (ANN) models previously developed by the author, as well as some of the most commonly available methods. The results indicate that the proposed EPR models agree well with (or better than) the ANN models and significantly outperform the other existing methods. The advantage of EPR technique over ANNs is that EPR generates transparent and well-structured models in the form of simple and easy-to-use hand calculation formulae that can be readily used by practising engineers.

dc.publisherTaylor and Francis
dc.subjectevolutionary polynomial regression
dc.subjectbearing capacity
dc.subjectground anchors
dc.subjectpile foundations
dc.subjectpullout capacity
dc.subjectshallow foundations
dc.subjectgeotechnical engineering
dc.titleUse of evolutionary computing for modelling some complex problems in geotechnical engineering
dc.typeJournal Article
dcterms.source.titleGeomechanics & Geoengineering: An International Journal

The Version of Record of this manuscript has been published and is available in Geomechanics & Geoengineering: An International Journal. 2015. <a href=""></a>

curtin.departmentDepartment of Civil Engineering
curtin.accessStatusOpen access

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