Presenter/Author Information

Jiří Hřebíček
Jan Pesl

Keywords

modelling, uncertainty analysis, symbolic algebraic computation, air pollution, transport

Start Date

1-7-2006 12:00 AM

Description

The important characteristic feature of 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). Many parameters in algorithms and their mathematical formulations are substituted by empirical constants in praxis, although it is well known that their values are very volatile and input data are not validated. 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 current ICT tools for the implementation of mathematical models with formula and data uncertainties. The Checkland’s soft system methodology is modified for its use by current ICT in environmental modelling with uncertainties. Further, results of the case study for the transport influence and all the related air pollution in the Czech Republic are presented. Various approaches for solving uncertainty with the computer algebra system Maple are simulated. The modification of the model COPERT III developed in Maple is almost free of any guessed emp irical values, but the results are still crisp enough and they are as useful (or more useful because of solving input volatility problem) as the original ones to analyze the situation and allow thinking about improvements of this specific environmental model.

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Jul 1st, 12:00 AM

Current Trends In Environmental Modelling With Uncertainty.

The important characteristic feature of 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). Many parameters in algorithms and their mathematical formulations are substituted by empirical constants in praxis, although it is well known that their values are very volatile and input data are not validated. 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 current ICT tools for the implementation of mathematical models with formula and data uncertainties. The Checkland’s soft system methodology is modified for its use by current ICT in environmental modelling with uncertainties. Further, results of the case study for the transport influence and all the related air pollution in the Czech Republic are presented. Various approaches for solving uncertainty with the computer algebra system Maple are simulated. The modification of the model COPERT III developed in Maple is almost free of any guessed emp irical values, but the results are still crisp enough and they are as useful (or more useful because of solving input volatility problem) as the original ones to analyze the situation and allow thinking about improvements of this specific environmental model.