Application of artificial neural network and excel solver on the reactive 19 dye removal from aqueous solution using biochar from pineapple peels. - Balo, Ela Marie P. (2022.)
Experimental adsorption studies generate results that are only specific to the independent variables utilized in the research. Thus, the development of Artificial Neural Network (ANN) models is relevant in determining the trends and implications necessary to predict future results given a different input value. This study focused on investigating the applicability of ANN modeling on the Reactive Blue 19 (RB19) dye removal from aqueous solution using biochar from pineapple peels. Independent variables of Activation Temperature (°C), Adsorbent Dose (g), Initial Dye Concentration (ppm), and Contact Time (h) of a Response Surface Methodology (RSM) Experimental Data were treated as the input, while the target variable was the Dye Removed (ppm). Levenberg-Marquardt Algorithm was found to be the most applicable, where an optimum MSE of 0.27 and an R2 of 0.9996 were generated. Moreover, testing for the predicted Dye Removed resulted in an average relative error of 1.02% which is a good indicator that the predicted values were close to the original experimental values. The code generated from the ANN was tested using the parameters used in the isotherm and kinetic data, where the predicted value for the Dye Removed resulted into an average relative error of 0.84% and 2.23%, respectively. This suggests that the concentration of the actual and the predicted Dye Removed were close with a minimal deviation. Sensitivity Analysis showed that the Initial Dye Concentration contributed the most, with the highest weight of 77.32%, while the Contact Time obtained the lowest weight with 2.98%. The Nonlinear Isotherm and Kinetic Models gave better approximations with lower residuals and higher r-squared values. Also, the calculated nonlinear values for the amount of solute adsorbed was close to the experimentally determined data.
Thesis (Undergraduate, Bachelor of Science in Chemical Engineering) School of Technology, University of the Philippines Visayas, Miagao, Iloilo. 2022.
Keywords: Pineapple peels