A neural network system for prediction of thermal resistance of textile fabrics

The objective of this paper is to report a study on the predictability of the steady-state and transient thermal properties of fabrics using a feed-forward, back-propagation artificial neural network system. A comparison was made with two different network architectures, one with two sequential networks working in tandem fed with a common input and another with a single network that gave two outputs. A three-layered network was used in both the cases. The networks were then subjected to a set of untrained inputs and the output thermal properties, namely thermal resistance and Q(max), were compared with the values obtained experimentally. The architecture with two networks working in tandem with a common set of inputs gave better results than the architecture with one set of inputs used to give two outputs.