Tensile Strength Prediction of Fiberglass Polymer Composites Using Artificial Neural Network Model

Highlighting the properties of polymer composites is a complex process given their great diversity and wide range in which characteristics could vary. An Artificial Neural Network model for predicting tensile strength was designed using LabVIEW software. The proposed developed randomly reinforced polymeric composite materials with 30%, 40% 50% fiber-glass. Volume fraction glass fibre has represented independent variable this study. dependence on volume investigated highlighted by modelling neural networks. behaves as computational system that data input into desired output network functions composed layers. training different architectures two hidden layers to produce best prediction results. For each layer number neurons varied be-tween 3 50.