Heat transfer correlations by symbolic regression

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@Article{Cai:2006:IJHMT,

• author = "Weihua Cai and Arturo Pacheco-Vega and Mihir Sen and K. T. Yang",
• title = "Heat transfer correlations by symbolic regression",
• journal = "International Journal of Heat and Mass Transfer",
• year = "2006",
• volume = "49",
• number = "23-24",
• pages = "4352--4359",
• month = nov,
• keywords = "genetic algorithms, genetic programming, Heat transfer, Correlations, Symbolic regression, Heat exchanger",
• DOI = "doi:10.1016/j.ijheatmasstransfer.2006.04.029",
• 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