Performance Evaluation of Imperialist Competitive and Genetic Algorithm for Estimating Groundwater Quality Parameters (Case Study: Bostanabad Plain)

Imperialist Competitive Algorithm (ICA) is a new socio-politically motivated global search strategy that has recently been introduced for dealing with different optimization tasks. The estimation of sodium adsorption ratio (SAR) and chloride content as example of groundwater quality parameters are much more time-consuming and expensive than water salinity measurement.For using this method, a numerical code was designed, and ICA algorithm calculated weight coefficients of the proposed function for the input data. The validation of the simulation with the ICA model showed that MSE in testing sample for SAR and chloride were 0.0134 and 0.0098, respectively. Also, R2 of validity for SAR and chloride were 0.93 and 0.952, respectively. This study was done based on the sample collected from the groundwater of Bostanabad plain, and could be generalized to other areas. The results of this study indicated high speed, convergence and power of the proposed method compared to genetic algorithm (GA) in estimation of sodium adsorption ratio (SAR) and chloride.