Evaluation of Copper Biosorption onto Date Palm (Phoenix dactylifera L.) Seeds with MLR and ANFIS Models

Date palm (Phoenix dactylifera L.) seeds, a waste product as a new, novel, and natural biosorbent, were used to remove Cu(II) ions from aqueous solutions by a batch sorption process. In this study first the comparison of a Multiple Linear Regression (MLR) and an Adaptive Neuro-Fuzzy Inference System (ANFIS) applied for modeling the sorption process is presented. Results were evaluated using Root Mean Squared Error (RMSE) and coefficient of determination (R2) as performance parameters. The experimental and model outputs displayed acceptable result for MLR and ANFIS; testing RMSE values were 0.6725 and 0.1716, and R2 values were 0.7594 and 0.9843, respectively. It was determined that Adaptive Neuro-Fuzzy Inference System (ANFIS) may be effectively used to predict the sorption of Cu(II) onto date palm seeds.