August 9, 2022
Gholam Hossein Roshani

Gholam Hossein Roshani

Academic rank: Associate professor
Address:
Education: Ph.D in Nuclear Engineering
Phone:
Faculty: Faculty of energy

Research

Title
Comparison of RSM and ANN Optimization Methods in Determining Antibacterial Properties of Cotton against E. coli
Type Article
Keywords
Researchers Mohammad Bameni Moghadam، M Montazer، Ali Nazari، Gholam Hossein Roshani، mohamad ataee

Abstract

In this paper, antibacterial properties of cotton fabric samples treated with nano titanium dioxide (NTO) and butane tetra carboxylic acid (BTCA) under different curing conditions (UV, High temp and UV-Temp) are compared. Response surface methodology (RSM) and artificial neural network (ANN) optimization methods are used to determine the antibacterial properties of samples and results of the two methods are compared with each other. The comparison between these two model optimization procedures shows clearly that ANN procedure can maximize E. coli reduction by 5 units more than that of RSM procedure.