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Environmental Modelling with Uncertainty

dc.contributor.authorHrebicek, Jiri
dc.contributor.authorHejc, Michal
dc.contributor.editorTochtermann, Klaus
dc.contributor.editorScharl, Arno
dc.date.accessioned2019-09-16T09:35:41Z
dc.date.available2019-09-16T09:35:41Z
dc.date.issued2006
dc.description.abstractThe characteristic feature of current environmental modelling is the complexity and uncertainty of its mathematical representation (uncertainty of formula). Imprecision of its input data is another characteristic feature, where it is not possible to omit influences of primary monitoring (e.g. gaps of data, errors of measuring facilities, human factor, etc). Nowadays, information and communication technology (ICT) capabilities are growing rapidly and applied mathematical software (e.g. computer algebra systems, statistical packages, etc) becomes more powerful to overcome problems with formula complexity and uncertainty. The basic methods how to deal with the data uncertainties are well known and standardized from the last century, but some of their comparisons and recommendations for environmental modelling are not known enough. Paper presents generalized approach and shows universal methodology how to use computer algebra based systems (CAS) for the implementation of mathematical models with formula and data uncertainties. The Checkland’s soft system methodology is modified for its use by CAS in environmental modelling with uncertainty. Various approaches for solving uncertainty with the computer algebra system Maple are presented. The modified model COPERT III with included uncertainty was developed in Maple and some results of the case study for the transport influence and all the related air pollution in the Czech Republic are presented.de
dc.description.urihttp://enviroinfo.eu/sites/default/files/pdfs/vol114/0215.pdfde
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/27485
dc.publisherShaker Verlag
dc.relation.ispartofManaging Environmental Knowledge
dc.relation.ispartofseriesEnviroInfo
dc.titleEnvironmental Modelling with Uncertaintyde
dc.typeText/Conference Paper
gi.citation.publisherPlaceAachen
gi.conference.date2006
gi.conference.locationGraz
gi.conference.sessiontitleEnvironmental Modeling

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