Neural Network on Photodegradation of Octylphenol using Natural and Artificial UV Radiation

Authors

  • Dana Melania POPA University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca, Calea Mănăştur 3-5, 400372 Cluj-Napoca, Romania.
  • Letiţia OPREAN “Lucian Blaga” University of Sibiu, Ion Raţiu 5-7, 550012, Sibiu, Romania.
  • Lorentz JÄNTSCHI University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca, Calea Mănăştur 3-5, 400372 Cluj-Napoca, Romania. & Technical University of Cluj-Napoca, 103-105 Muncii Bvd, 400641 Cluj-Napoca, Romania.

Keywords:

octylphenol, photodegradation, regression analysis, backward stepwise method, neural network, multilayer perceptron

Abstract

The present paper comes up with an experimental design meant to point out the factors interfering in octylphenol’s degradation in surface waters under solar radiation, underlining each factor’s influence on the process observable (concentration of p-octylphenol). Multiple linear regression analysis and artificial neural network (Multi-Layer Perceptron type) were applied in order to obtain a mathematical model capable to explain the action of UV-light upon synthetic solutions of OP in ultra-pure water (MilliQ type). Neural network proves to be the most efficient method in predicting the evolution of OP concentration during photodegradation process. Thus, determination in neural network’s case has almost double value versus the regression analysis.

Downloads

Published

22.09.2011

How to Cite

1.
POPA DM, OPREAN L, JÄNTSCHI L. Neural Network on Photodegradation of Octylphenol using Natural and Artificial UV Radiation. Appl Med Inform [Internet]. 2011 Sep. 22 [cited 2024 May 28];29(3):1-10. Available from: https://ami.info.umfcluj.ro/index.php/AMI/article/view/347

Issue

Section

Articles