Evolutionary computation-based approach for model error correction and calibration
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- @Article{Zechman:2007:AWR,
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author = "Emily M. Zechman and S. Ranji Ranjithan",
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title = "Evolutionary computation-based approach for model
error correction and calibration",
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journal = "Advances in Water Resources",
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year = "2007",
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volume = "30",
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number = "5",
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pages = "1360--1370",
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month = may,
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keywords = "genetic algorithms, genetic programming, Evolutionary
computation, Calibration, Model error correction",
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DOI = "doi:10.1016/j.advwatres.2006.11.013",
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size = "11 pages",
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abstract = "Calibration is typically used for improving the
predictability of mechanistic simulation models by
adjusting a set of model parameters and fitting model
predictions to observations. Calibration does not,
however, account for or correct potential
misspecifications in the model structure, limiting the
accuracy of modelled predictions. This paper presents a
new approach that addresses both parameter error and
model structural error to improve the predictive
capabilities of a model. The new approach
simultaneously conducts a numeric search for model
parameter estimation and a symbolic (regression) search
to determine a function to correct misspecifications in
model equations. It is based on an evolutionary
computation approach that integrates genetic algorithm
and genetic programming operators. While this new
approach is designed generically and can be applied to
a broad array of mechanistic models, it is demonstrated
for an illustrative case study involving water quality
modelling and prediction. Results based on extensive
testing and evaluation, show that the new procedure
performs consistently well in fitting a set of training
data as well as predicting a set of validation data,
and outperforms a calibration procedure and an
empirical model fitting procedure.",
- }
Genetic Programming entries for
Emily M Zechman
S Ranji Ranjithan
Citations