Modeling and estimation of cr (VI) efficiency using non-linear regression

Abstract

One of the most detrimental water pollutant is heavy metal ions. It increases in the rate of industrialization and causes severe health hazards on human beings. The removal of heavy metal ions from wastewater is essential before releasing them into the natural environment because of their toxicity. In this study, estimation of Cr (VI) removal from waste water was studied using nonlinear regression model. It contains mathematical equation of a complex chemical process. Therefore, the value of the proposed model is to be convenient and robust method to predict the Cr (VI) removal with minimum process knowledge. Adsorbent dosage, pH, temperature and initial concentration, were selected as the input variables, and Cr (VI) removal efficiency chosen as the output parameter of nonlinear model. The performance of the proposed model in this study was evaluated for Cr(VI) uptake rate in terms of root mean square error (RMSE) and correlation coefficient (R2). The validation confirms that the major advantage of this model is its capability to compute removal efficiency of Cr(VI) simply. The objective of this study was therefore to investigate the removal of Cr(VI) ions in aqueous solutions using non-linear regression model to explore the effects of factors on the adsorption. Thereby, the proposed model maintains a useful tool for prediction removal efficiency for Cr(VI).