In this study, an artificial neural network (ANN) is used for the prediction of tensile strength of nano titanium dioxide (TiO2) coated cotton. The coating process was performed by ultraviolet (UV) radiations. Later on, a backpropagation ANN algorithm trained with Bayesian regularization was applied to predict the tensile strength. For a comparative study, ANN results were compared with traditional methods including multiple linear regression (MLR) and polynomial regression analysis (PRA). The input conditions for the experiment were dosage of TiO2, UV irradiation time and temperature of the system. Simulation results elucidated that ANN model provides high performance accuracy than MLR and PRA. In addition, statistical analysis was also performed to check the significance of this study. The results show a strong correlation between predicted and measured tensile strength of nano TiO2-coated cotton with small error values.

Department of Machinery Construction Institute for Nanomaterials Advanced Technologies and Innovation Technical University of Liberec Studentská 1402 2 461 17 Liberec Czech Republic

Institute of Organic and Polymeric Materials National Taipei University of Technology No 1 Section 3 Zhongxiao East Road Taipei 106 Taiwan

Laboratory of Signal Image and Energy Mastery Electrical Engineering Department University of Tunis ENSIT Tunis 1008 Tunisia

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