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Young, P.C. (1998) Data-based mechanistic modelling of environmental,
ecological, economic and engineering systems. Environmental Modelling and
Software, 13, 105-122.
Mathematical modelling in the natural and engineering sciences is most
often dominated by a philosophy of deterministic reductionism. Moreover,
many of the 'simulation' models that emerge from this approach to modelling
are very large and so difficult to identify, estimate (i.e. calibrate) and
validate in rigorous statistical terms. In this situation, it seems
sensible to consider alternative modelling strategies which overtly
acknowledge these data-based modelling difficulties and address the very
real problems of calibration and validation associated with the dynamic
modelling of complex systems from time series data. This paper outlines a
Data-Based Mechanistic (DBM) modelling philosophy which attempts to address
some of these problems and illustrates its wide-ranging practical utility
through seven examples in areas ranging from the natural environment,
through ecology and macro-economics to engineering.
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12/10/01 - PGM.