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dc.relation.isnodouble32121*
dc.contributor.authorRasouli, Mohammad
dc.contributor.supervisorProf. Hamid Nikraz
dc.contributor.supervisorAssoc. Prof. Faisal Anwar
dc.date.accessioned2017-01-30T09:52:13Z
dc.date.available2017-01-30T09:52:13Z
dc.date.created2015-09-02T04:09:03Z
dc.date.issued2014
dc.identifier.urihttp://hdl.handle.net/20.500.11937/669
dc.description.abstract

In this research a new generalized regression neural network (GRNN) model has been researched to estimate the distribution of journey to work trips. As a case study, the model was applied to the journey to work trips in the City of Mandurah in Western Australia. The results of the GRNN model were compared with the well-known doubly-constrained gravity model and the Back-Propagation model and its superiority over these models has been demonstrated.

dc.languageen
dc.publisherCurtin University
dc.titleTrip distribution modelling using neural network
dc.typeThesis
dcterms.educationLevelPhD
curtin.departmentSchool of Civil and Mechanical Engineering
curtin.accessStatusOpen access


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