Abstract Accurate prediction of water surface profile in an open channel is the key to solving numerous critical engineering problems. The goal current research predict a compound with converging floodplains using machine learning approaches, including gene expression programming (GEP), artificial neural networks (ANNs), and support vector machines (SVMs), terms both geometric flow variables, a...

Evapotranspiration (ET) is a significant aspect of the hydrologic cycle, notably in irrigated agriculture. Direct approaches for estimating reference evapotranspiration (ET0) are either difficult or need large number inputs that not always available from meteorological stations. Over 6-year period (2006–2011), this study compares Feed Forward Neural Network (FFNN), Radial Basis Function (RBFNN)...

Abstract This piece of study attempts to accurately anticipate the apparent viscosity viscoelastic surfactant (VES) based self-diverting acids as a function VES concentration, temperature, shear rate, and pH value. The focus not only is on generating computer-aided models but also developing straightforward reliable explicit mathematical expression. Towards this end, Gene Expression Programming...

This work presents a quantitative predicting likely acid mine drainage (AMD) generation process throughout tailing particles resulting from the Sarcheshmeh copper mine in the south of Iran. Indeed, four predictive relationships for the remaining pyrite fraction, remaining chalcopyrite fraction, sulfate concentration, and pH have been suggested by applying the gene expression programming (GEP) a...

Finding functions whose accuracies change significantly between two classes is an interesting work. In this paper, this kind of functions is defined as class contrast functions. As Gene Expression Programming (GEP) can discover essential relations from data and express them mathematically, it is desirable to apply GEP to mining such class contrast functions from data. The main contributions of ...

Artificial neural network (ANN), pseudo second-order kinetic, and gene expression programming (GEP) models were constructed to predict removal efficiency of Lanaset Red G (LR G) using lentil straw (LS) based on 1152 experimental sets. The sorption process was dependent on adsorbent particle size, pH, initial dye concentration, and contact time. These variables were used as input to construct a ...

In this study, Gene Expression Programming (GEP) is used in modeling the deflection basins measured on the surface of the flexible pavements. Backcalculation of the pavement layer moduli are well-accepted procedures for the evaluation of the structural capacity of pavements. The ultimate aim of the backcalculation process from Nondestructive Testing (NDT) results is to estimate the pavement mat...

In diagnosis of lung cancer, rapid distinction between small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) tumors is very important. Serum markers, including lactate dehydrogenase (LDH), C-reactive protein (CRP), carcino-embryonic antigen (CEA), neurone specific enolase (NSE) and Cyfra21-1, are reported to reflect lung cancer characteristics. In this study classification of lun...

Gene expression programming (GEP) is, like genetic algorithms (GAs) and genetic programming (GP), a genetic algorithm as it uses populations of individuals, selects them according to fitness, and introduces genetic variation using one or more genetic operators [1]. The fundamental difference between the three algorithms resides in the nature of the individuals: in GAs the individuals are linear...

Abstract Soil stabilization is an in situ soil treatment which soils are mixed with cementitious or other chemical stabilizing agents. Determining the unconfined compressive strength (UCS) of stabilized a principal task design and construction ground improvement. Hence, this study aims to develop reliable predictive model for UCS clay common binders using gene-expression programming (GEP) techn...