Using individual-level models to model spatio-temporal combustion dynamics

dc.contributor.advisorDeardon, R.
dc.contributor.advisorFeng, Z.
dc.contributor.authorVrbik, Irene
dc.date.accessioned2021-04-16T15:12:12Z
dc.date.available2021-04-16T15:12:12Z
dc.date.copyright2010
dc.degree.departmentDepartment of Mathematics and Statisticsen_US
dc.degree.grantorUniversity of Guelphen_US
dc.degree.nameMaster of Scienceen_US
dc.description.abstractIndividual-level models (ILMs), as defined by Deardon et al. (2010), are a class of models originally designed to model the spread of infectious disease. However, they can also be considered as a tool for modelling the spatio-temporal dynamics of fire. We consider the much simplified problem of modelling the combustion dynamics on a piece of wax paper under relatively controlled conditions. The models are fitted in a Bayesian framework using Markov chain Monte Carlo (MCMC) methods. The focus here is on choosing a model that best fits the combustion pattern.en_US
dc.identifier.urihttps://hdl.handle.net/10214/24863
dc.language.isoen
dc.publisherUniversity of Guelphen_US
dc.rights.licenseAll items in the Atrium are protected by copyright with all rights reserved unless otherwise indicated.
dc.subjectindividual-level modelsen_US
dc.subjectspatio-temporal dynamicsen_US
dc.subjectfireen_US
dc.subjectcombustion dynamicsen_US
dc.subjectcombustion patternsen_US
dc.titleUsing individual-level models to model spatio-temporal combustion dynamicsen_US
dc.typeThesisen_US

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