Application of response surface methodology and artificial neural network methods in modelling and optimization of biosorption process

• Theoretical background of optimization methods (RSM and ANN).
• Design of experiments as a tool for improving efficiency of the processes.
• Optimization of biosorption process using response surface methodology (RSM).
• Optimization of biosorption process using artificial neural networks (ANN).

A review on the application of response surface methodology (RSM) and artificial neural networks (ANN) in biosorption modelling and optimization is presented. The theoretical background of the discussed methods with the application procedure is explained. The paper describes most frequently used experimental designs, concerning their limitations and typical applications. The paper also presents ways to determine the accuracy and the significance of model fitting for both methodologies described herein. Furthermore, recent references on biosorption modelling and optimization with the use of RSM and the ANN approach are shown. Special attention was paid to the selection of factors and responses, as well as to statistical analysis of the modelling results.