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A Neural Network System for Prediction of Thermal Resistance of Textile Fabrics

2007; SAGE Publishing; Volume: 77; Issue: 1 Linguagem: Inglês

10.1177/0040517506070065

1746-7748

Debarati Bhattacharjee, Vijay Kumar Kothari,

Surface Roughness and Optical Measurements

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 Qmax, 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.