Granularity and disaggregation in compositional modelling with applications to ecological systems

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dc.contributor.author Keppens, Jeroen
dc.contributor.author Shen, Qiang
dc.date.accessioned 2008-01-15T16:20:17Z
dc.date.available 2008-01-15T16:20:17Z
dc.date.issued 2006-12
dc.identifier.citation Keppens , J & Shen , Q 2006 , ' Granularity and disaggregation in compositional modelling with applications to ecological systems ' Applied Intelligence , vol 25 , no. 3 , pp. 269-292 . , 10.1007/s10489-006-0107-y en
dc.identifier.issn 1573-7497
dc.identifier.other PURE: 74294
dc.identifier.other dspace: 2160/426
dc.identifier.uri http://hdl.handle.net/2160/426
dc.description J. Keppens and Q. Shen. Granularity and disaggregation in compositional modelling with applications to ecological systems. Applied Intelligence, 25(3):269-292, 2006. en
dc.description.abstract In the past decade, compositional modelling (CM) has established itself as the predominant knowledge-based approach to construct mathematical (simulation) models automatically. Although it is mainly applied to physical systems, there is a growing interest in applying CM to other domains, such as ecological and socio-economic systems. Inspired by this observation, this paper presents a method for extending the conventional CM techniques to suit systems that are fundamentally presented by interacting populations of individuals instead of physical components or processes. The work supports building model repositories for such systems, especially in addressing the most critical outstanding issues of granularity and disaggregation in ecological systems modelling. en
dc.format.extent 24 en
dc.language.iso eng
dc.relation.ispartof Applied Intelligence en
dc.subject Model-based reasoning en
dc.subject Compositional modelling en
dc.subject Granularity en
dc.subject Disaggregation en
dc.subject Ecological systems en
dc.title Granularity and disaggregation in compositional modelling with applications to ecological systems en
dc.type Text en
dc.type.publicationtype Article (Journal) en
dc.identifier.doi http://dx.doi.org/10.1007/s10489-006-0107-y
dc.contributor.institution Department of Computer Science en
dc.contributor.institution Advanced Reasoning Group en
dc.description.status Peer reviewed en


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