Trip distribution modelling using neural network
Access Status
Open access
Authors
Rasouli, Mohammad
Date
2014Supervisor
Prof. Hamid Nikraz
Assoc. Prof. Faisal Anwar
Type
Thesis
Award
PhD
Metadata
Show full item recordSchool
School of Civil and Mechanical Engineering
Collection
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.
Related items
Showing items related by title, author, creator and subject.
-
Alkroosh, Iyad Salim Jabor (2011)This thesis presents the development of numerical models which are intended to be used to predict the bearing capacity and the load-settlement behaviour of pile foundations embedded in sand and mixed soils. Two artificial ...
-
Amiri, Amirpiran (2013)The alumina industry provides the feedstock for aluminium metal production and contributes to around A$6 billion of Australian exports annually. One of the most energy-intensive parts of alumina production, with a strong ...
-
Fulton, B.; Jones, Tod; Boschetti, F.; Sporcic, M.; De La Mare, W.; Syme, Geoffrey; Dzidic, Peta; Gorton, R.; Little, L.; Dambacher, G.; Chapman, K. (2011)We describe the different types of models we used as part of an effort to inform policy-making aiming at the management of the Ningaloo coast in the Gascoyne region, Western Australia. This provides an overview of how ...