Using Artificial Neural Network Modeling in Predicting the Amount of Methyl Violet Dye Absorption by Modified Palm Fiber

Abstract

Bio-absorbent palm fiber was applied for removal of cationic violet methyl dye from water solution. For this purpose, a solid phase extraction method combined with the artificial neural network (ANN) was used for preconcentration and determination of removal level of violet methyl dye. This method is influenced by factors such as pH, the contact time, the rotation speed, and the adsorbent dosage. In order to find a suitable model of parameters and calculate the desired output, two radial basis function (RBF) and multi-layer perceptron (MLP) non-recursive functions, which are among widely used artificial neural networks, were used for training the input data. The performance of this method is tested by common statistical parameters including RMSE, MAE, and CE. The results show that the artificial neural network algorithm has a good performance in simulating and predicting the removal of violet methyl dye.