Heat transfer correlations by symbolic regression
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- @Article{Cai:2006:IJHMT,
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author = "Weihua Cai and Arturo Pacheco-Vega and Mihir Sen and
K. T. Yang",
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title = "Heat transfer correlations by symbolic regression",
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journal = "International Journal of Heat and Mass Transfer",
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year = "2006",
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volume = "49",
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number = "23-24",
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pages = "4352--4359",
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month = nov,
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keywords = "genetic algorithms, genetic programming, Heat
transfer, Correlations, Symbolic regression, Heat
exchanger",
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DOI = "doi:10.1016/j.ijheatmasstransfer.2006.04.029",
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abstract = "We describe a methodology that uses symbolic
regression to extract correlations from heat transfer
measurements by searching for both the form of the
correlation equation and the constants in it that
enable the closest fit to experimental data. For this
purpose we use genetic programming modified by a
penalty procedure to prevent large correlation
functions. The advantage of using this technique is
that no initial assumption on the form of the
correlation is needed. The procedure is tested using
two sets of published experimental data, one for a
compact heat exchanger and the other for liquid flow in
a circular pipe. In both situations, predictive errors
from correlations found from symbolic regression are
smaller than their published counterparts. A parametric
analysis of the penalty function is also carried out.",
- }
Genetic Programming entries for
Weihua Cai
Arturo Javier Pacheco Vega
Mihir Sen
K T Yang
Citations