Applying genetic programming in estimation of frost layer thickness on horizontal and vertical plates at ultra-low temperature
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @Article{HOSSEINI:2021:IJR,
-
author = "S. H. Hosseini and M. A. Moradkhani and
M. Valizadeh and G. Ahmadi",
-
title = "Applying genetic programming in estimation of frost
layer thickness on horizontal and vertical plates at
ultra-low temperature",
-
journal = "International Journal of Refrigeration",
-
volume = "125",
-
pages = "113--121",
-
year = "2021",
-
ISSN = "0140-7007",
-
DOI = "doi:10.1016/j.ijrefrig.2020.12.035",
-
URL = "https://www.sciencedirect.com/science/article/pii/S0140700720305296",
-
keywords = "genetic algorithms, genetic programming, Frost layer
thickness, Smart model, Cryogenic condition, Horizontal
and vertical plates, Epaisseur de la couche de givre,
Modele intelligent, Condition cryogenique, Plaques
verticales et horizontales",
-
abstract = "In this study, the intelligent method of genetic
programming (GP) was used for developing predictive
models for estimating the frost layer thickness under
natural and forced convection on ultra-low temperature
surfaces. The affecting dimensionless parameters were
used as GP input variables, and realistic empirical
correlations were developed for estimating the frost
thickness under different conditions. The coefficient
of determination of 0.9731, 0.9812, and 0.9906, and
average absolute relative error of 6.52percent,
11.65percent, and 2.87percent, were obtained by the
developed models for natural convection on vertical
plates, natural convection on horizontal plates, and
forced convection on horizontal plates, respectively.
The physical trends of the developed models were
evaluated by comparing the model predictions with the
experimental data for different operating conditions,
and reasonable agreements were obtained. The same
experimental database was also compared to some
existing correlations for ordinary-low temperature
surfaces, but they failed to provide reasonable
estimates for the data",
- }
Genetic Programming entries for
Seyyed Hossein Hosseini
Mohammad Amin Moradkhani
Mohammadreza Valizadeh
Goodarz Ahmadi
Citations