Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi

Öz

In this study,
prediction of Cu²⁺ biosorption to tobacco leaf, and the organic
pollution (COD) created by this process on the biosorption system using
Artificial Neural Network (ANN) models was investigated. In this scope, 26 data
obtained from the biosorption process from the model were normalized and used
in the comparison. For the development of the model, data regarding pH,
temperature, and biosorbent dosage were used in the input layer, and COD was
predicted in the output layer. In this model, five different models were
created, and the most suitable model was determined with 3-4-1 structure and
0,991 R² value. High R² values were also obtained in
other model structures. The statistical comparison of the predictions obtained
from ANN models with the measurement results shows that the models have good
predicting capability and can be used for prediction purpose.