Gene-expression programming for transverse mixing coefficient

SummaryThis study presents gene-expression programming (GEP), which is an extension of genetic programming (GP), as an alternative approach to predict the transverse mixing coefficient in open channel flows. Laboratory data were collected in the present study and also from the literature for the transverse mixing coefficient covering wide range of flow conditions. These data were used for the development and testing of the proposed method. A functional relation for the estimation of transverse mixing coefficient has been developed using GEP. The proposed GEP approach produced satisfactory results compared to the existing predictors for the transverse mixing coefficient.

► This study presents gene-expression programming (GEP) to predict the transverse mixing coefficient in open channel flows.
► A functional relation for transverse mixing coefficient has been developed using GEP.
► The proposed GEP approach produces satisfactory results compared to the existing predictors for the mixing coefficient.