Heat Transfer Correlations in an Air-Water Fin-Tube Compact Heat Exchanger by Symbolic Regression
Created by W.Langdon from
gp-bibliography.bib Revision:1.8129
- @InProceedings{Pacheco-Vega:2003:IMECE,
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author = "Arturo Pacheco-Vega and Weihua Cai and Mihir Sen and
K. T. Yang",
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title = "Heat Transfer Correlations in an Air-Water Fin-Tube
Compact Heat Exchanger by Symbolic Regression",
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booktitle = "ASME International Mechanical Engineering Congress and
Exposition (IMECE2003)",
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year = "2003",
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volume = "3",
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pages = "23--28",
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address = "Washington, DC, USA",
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month = nov # " 15-21",
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publisher = "ASME",
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keywords = "genetic algorithms, genetic programming",
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ISBN = "0-7918-3718-1",
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DOI = "doi:10.1115/IMECE2003-41977",
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abstract = "In the present study we propose the application of
evolutionary algorithms to find correlations that can
predict the performance of a compact heat exchanger.
Genetic programming (GP) is a search technique in which
computer codes, representing functions as parse trees,
evolve as the search proceeds. As a symbolic regression
approach, GP looks for both the functional form and the
coefficients that enable the closest fit to
experimental data. Two different data sets are used to
test the symbolic regression capability of genetic
programming, the first being artificial data from a
one-dimensional function, while the second are data
generated by previously determined correlations from
experimental measurements of a single-phase air-water
heat exchanger. The results demonstrate that the
correlations found by symbolic regression are able to
predict well the data from which they were determined,
and that the GP technique may be suitable for modelling
the nonlinear behaviour of heat exchangers. It is also
shown that there is not a unique answer for the
best-fit correlation from this procedure. The advantage
of using genetic programming as symbolic regression is
that no initial assumptions on the functional forms are
needed, which is contrary to the traditional
approach.",
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notes = "University Autonoma de San Luis Potosi, San Luis
Potosi, Mexico",
- }
Genetic Programming entries for
Arturo Javier Pacheco Vega
Weihua Cai
Mihir Sen
K T Yang
Citations