Jornal de Engenharia Química Avançada

Abstrato

Artificial Neural Network Modelling for the Removal of Fe (III) from Aqueous Solutions Using Chitosan Magnetite Nano Composites (CMNs)

Mini Namdeo, Rama Mehta, Mehta VK and Vijaya Agarwala

A two-layer Artificial Neural Network (ANN) model was engendered tosoothsay the deliberation efficacy of Fe (II) particles from fluid arrangement utilizing chitosan magnetite nano composites (CMNs). The sorbet stock arrangement was yare by dissolving a pre-computed amount of FeCl3 in twofold refined water to give last fixation 100 mgl−1. The stock arrangement was debilitated to get standard arrangements with fixation in the scope of 5-30 mgl−1and their last pH was transmuted in accordance with 4.5. Fifty millilitres of FeCl3 arrangement of fancied focus was put in a 125 ml Erlenmeyer flagon containing 0.02 g of CMN sorbent. A period of 3 hours was discovered adequate to accomplish the balance. The ANN model was intended to suspect sorption efficacy of CMNs for target metal particle by amalgamating back spread (BP) with guideline segment examination. A sigmoid axon was utilized as exchange capacity for information and yield layer. The Levenberg-Marquardt calculation (LMA) was connected, giving a base estimation of mean squared mistake (MSE) for preparing and cross approbation at the 6th place of decimal.