نوع مقاله : مقاله پژوهشی
موضوعات
عنوان مقاله English
نویسندگان English
In this article, the effect of operating conditions and aqueous solution on the CO₂ absorption rate was modeled using response surface methodology (RSM) and an artificial neural network (ANN). The network inputs included temperature, pressure, piperazine percentage/potassium carbonate as the solvent, with the mass transfer flux of CO₂ as the output. The MLP (multi-layer perceptron) network was trained with three hidden layers containing 10, 40, and 10 neurons, respectively, using the Levenberg-Marquardt training function. The MLP network with three layers and 60 neurons, trained with the Trainlm learning function, achieved an MSE of 0.0018616 and an R² of 0.99924. The RBF (radial basis function) network also reached an MSE of 0.0004 and an R² of 0.99849 after 200 epochs. Overall, the MLP network showed better results as it achieved high accuracy in less time.
کلیدواژهها English
