Influence of Ultrasonic and Microwave Irradiation on Cation Exchange Properties of Clay Material

A. Švarc, Š. Ukić, S. Radojević Lacković, B. Ðuričić, M. Novak and T. Bolanča

Abstract
This study deals with optimization of the clay activation process using artificial neural network models and multi-objective optimization function. Different artificial neural network models were used for description of the relation between clay sorption capacity and the activation treatment process (power and time of clay exposure to ultrasonic and/or microwave irradiation). Two methodologies (feed-forward and cascade-forward) in combination with five different training algorithms (random order incremental training with learning functions, resilient backpropagation, one-step secant backpropagation, Levenberg-Marquardt backpropagation, Bayesian regularization backpropagation) were applied in order to obtain an optimal artificial neural network model. The optimal artificial neural network model showed good predictive ability (relative error 6.02 % based on external validation data set). In-house developed multi-objective criteria function was used in combination with the developed artificial neural network model and calculated optimal activation was determined (5 minutes of ultrasonic 120 W and microwave 60 W treatment) increasing the sorption capacity by 15 %.

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Keywords
Clay activation, multi-objective optimization, artificial neural networks