Please use this identifier to cite or link to this item: http://nopr.niscair.res.in/handle/123456789/24535
Title: Engineering design of polyester-viscose blended suiting fabrics using radial basis function network: Part I — Prediction of fabric low-stress mechanical properties
Authors: Behera, B K
Muttagi, S B
Keywords: Engineering design;Neural network;Polyester-viscose blend;Prediction error;Radial basis function
Issue Date: Sep-2006
Publisher: NISCAIR-CSIR, India
IPC Code: Int. Cl.8 G06N3/02
Abstract: A complete engineering design of polyester-viscose blended suiting fabrics has been presented using radial basis function neural network algorithm. Fabric low-stress mechanical properties, such as extension, bending rigidity, shear rigidity, breaking strength have been predicted from the structural parameters of the fabric such as weave, yarn tex, thread density, crimp, fabric mass and fabric cover. It is observed that the radial basis function neural network could successfully predict the trends in variation of fabric property with corresponding change in structural parameters.
Page(s): 401-408
URI: http://hdl.handle.net/123456789/24535
ISSN: 0975-1025 (Online); 0971-0426 (Print)
Appears in Collections:IJFTR Vol.31(3) [September 2006]

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