| Literature DB >> 24495798 |
Anna Witek-Krowiak1, Katarzyna Chojnacka2, Daria Podstawczyk1, Anna Dawiec1, Karol Pokomeda1.
Abstract
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.Keywords: Artificial neural networks; Biosorption; Design of experiments; Optimization; Response surface methodology
Mesh:
Year: 2014 PMID: 24495798 DOI: 10.1016/j.biortech.2014.01.021
Source DB: PubMed Journal: Bioresour Technol ISSN: 0960-8524 Impact factor: 9.642