Neural Network on Photodegradation of Octylphenol using Natural and Artificial UV Radiation
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.
octylphenol, photodegradation, regression analysis, backward stepwise method, neural network, multilayer perceptron