Logo des Repositoriums
 

Integrating Knowledge-Driven and Data-Driven Approaches to Modeling

dc.contributor.authorTodorovski, Ljupe
dc.contributor.authorDžeroski, Sašo
dc.contributor.editorMinier, Philippe
dc.contributor.editorSusini, Alberto
dc.date.accessioned2019-09-16T09:34:04Z
dc.date.available2019-09-16T09:34:04Z
dc.date.issued2004
dc.description.abstractIn this paper, we present a modeling framework that integrates the knowledge-based theoretical approach to modeling with the data-driven empirical modeling of dynamic systems. The framework allows for integration of modeling knowledge specific to the domain of interest in the process of model induction from measured data. The knowledge is organized around the central notion of basic processes in the domain, their models, and includes guidelines for combining models of individual processes into a model of the entire observed system. We present a method for automated translation of the knowledge into the operational form of grammars that constrain the space of candidate models considered during the induction process. The developed framework is applied to two tasks of modeling dynamic systems from noisy measurement data in the domains of population and hydro dynamics.de
dc.description.urihttp://enviroinfo.eu/sites/default/files/pdfs/vol109/0215.pdfde
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/27195
dc.publisherEditions du Tricorne
dc.relation.ispartofSh@ring – EnviroInfo 2004
dc.relation.ispartofseriesEnviroInfo
dc.titleIntegrating Knowledge-Driven and Data-Driven Approaches to Modelingde
dc.typeText/Conference Paper
gi.citation.publisherPlaceGeneva
gi.conference.date2004
gi.conference.locationGeneva
gi.conference.sessiontitleTrack 2: New Developments in Sharing Technologies

Dateien