Artificial Neural Network Modeling of The Removal of Cr (VI) on by Polymeric Calix[6]arene in aqueous solutions

Year 2020, Volume: 12 Issue: 1, 13 - 20, 31.01.2020

Abdullah Erdal Tümer

https://doi.org/10.29137/umagd.472269

Cited By: 1

Abstract

The artificial neural network-based model was
developed to predict the sorption capacity and removal efficiency of calixarene
for Cr(VI) in aqueous solutions. The input variables were initial concentration
of Cr(VI), adsorbent dosage, contact time, and pH, while the sorption capacity
and the removal efficiency were considered as output. They have been used for
the training and simulation of the network in the current work. The training
results were tested using the input data (simulated data) that were not shown
to the network. According to the indicator, the optimum and most reliable model
was found based on the test results.

Keywords

Artificial Neural Network, Modeling, Sorption, Removal Efficiency, Sorption Capacity

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