Automatic reactor model synthesis with genetic programming
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gp-bibliography.bib Revision:1.8010
- @Article{Duerrenmatt:2012:WST,
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author = "David J. Duerrenmatt and Willi Gujer",
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title = "Automatic reactor model synthesis with genetic
programming",
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journal = "Water Science \& Technology",
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year = "2012",
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volume = "65",
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number = "4",
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pages = "765--772",
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month = "1 " # feb,
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keywords = "genetic algorithms, genetic programming, grammar-based
genetic programming, hydraulic reactor systems, water
utility, modelling, operating data",
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ISSN = "0273-1223",
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URL = "http://www.iwaponline.com/wst/06504/0765/065040765.pdf",
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DOI = "doi:10.2166/wst.2012.913",
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size = "8 pages",
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abstract = "Successful modelling of waste water treatment plant
(WWTP) processes requires an accurate description of
the plant hydraulics. Common methods such as tracer
experiments are difficult and costly and thus have
limited applicability in practice; engineers are often
forced to rely on their experience only. An
implementation of grammar-based genetic programming
with an encoding to represent hydraulic reactor models
as program trees should fill this gap: The encoding
enables the algorithm to construct arbitrary reactor
models compatible with common software used for WWTP
modeling by linking building blocks, such as continuous
stirred-tank reactors. Discharge measurements and
influent and effluent concentrations are the only
required inputs. As shown in a synthetic example, the
technique can be used to identify a set of reactor
models that perform equally well. Instead of being
guided by experience, the most suitable model can now
be chosen by the engineer from the set. In a second
example, temperature measurements at the influent and
effluent of a primary clarifier are used to generate a
reactor model. A virtual tracer experiment performed on
the reactor model has good agreement with a tracer
experiment performed on-site.",
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notes = "Sewage treatment plant",
- }
Genetic Programming entries for
David J Duerrenmatt
Willi Gujer
Citations