Deniz Baş

TL;DR: This paper looked at some of the RSM articles published during the last few years to identify common mistakes made in the application and the limitations of RSM.

TL;DR: In this paper, the estimation capabilities of response surface methodology (RSM) and artificial neural networks (ANN) in a biochemical process were investigated, where an enzymatic reaction catalyzed by amyloglucosidase was selected as the model biochemical process.

TL;DR: In this paper, the authors investigated the usability of ANN for the estimation of enzymatic reaction rate and found that the network was trained till the mean square value between the targets and the outputs obtained was 1 × 10 −4.

TL;DR: Although the samples showed similar compositional properties, there were significant variations in the ripening parameters and flavour attributes, and the most preferred cheeses were manufactured in two neighbouring provinces located in the north-west of the country.

TL;DR: An application of artificial neural networks (ANNs) to determine kinetics of enzymatic reactions and to estimate kinetic constants and the results indicate that the time courses obtained from the developed program fit more properly to the experimental data than that from conventional method.