Comparative modeling of fluoride biosorption onto waste Gossypium hirsutum seed microwave-bichar using response surface methodology and artificial neural networks

Abstract

Biochar prepared from waste Gossypium hirsutum seeds using microwave activation were examined for adsorptive removal of fluoride ions. The key and cooperative effects of process variables were used to develop a prediction models for optimization for fluoride removal using response surface methodology(RSM) and Artificial neural network(ANN) model. The ANN model also performed here to predict the optimal condition for evaluation of fluoride adsorption onto waste gossypium hirsutum seed microwave-bichar using MATLAB. The comparison of coefficient of determination values show that RSM(0.9911) was superior in predicting the adsorption of fluoride to ANN (0.9702) model.