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A critical review on prediction of functional & performance attributes of textiles by artificial neural network

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Title A critical review on prediction of functional & performance attributes of textiles by artificial neural network
 
Creator Jhanji, Y
Kothari, V K
Gupta, Deepti
 
Subject Artificial neural network
Comfort properties
Neurons
Thermo-physiological properties
Textiles
 
Description 252-258
Prediction of functional and performance properties of textiles before the actual commencement of fabric production and
testing can serve as an effective tool in characterization and designing of fabrics for any desired application. The thermophysiological
properties of textile materials can be predicted by a variety of models, such as statistical, mechanistic and
artificial neural network models. Statistical models can give good prediction performance, provided a large data set is
presented to make the model and relationship exists between input parameters and response variables. The effect of input
parameters on thermo-physiological properties of fabrics cannot be studied in isolation, owing to interdependence and
nonlinear relationship of parameters with each other. Statistical models fail to present satisfactory analysis of relationship in
such cases. Mechanistic models are useful tools in understanding the fundamentals and physics involved in heat, moisture
and liquid transfer through textiles. However, the assumptions considered in the simplification of mechanistic models may
not be valid in all conditions and can lead to high prediction errors in real conditions, owing to inherent variability in the
textile structures. Moreover the model becomes more complicated as the number of parameters and assumptions increase,
thereby limiting the model’s accuracy of prediction. Artificial neural network is a powerful and potent modelling tool which
can understand any complex relationship between input and response variables and predicts the thermo-physiological
properties of fabrics by considering all fabric parameters at a time. The network exhibits the ability of simulating the
functioning of a biological neuron and, in turn, each network component poses analogy to the actual constituents or
operations of a biological neuron. In this study, an attempt has been made to highlight the significance of artificial neural
network in prediction of comfort properties of textiles.
 
Date 2022-06-30T10:01:50Z
2022-06-30T10:01:50Z
2022-06
 
Type Article
 
Identifier 0975-1025 (Online); 0971-0426 (Print)
http://nopr.niscpr.res.in/handle/123456789/59991
 
Language en
 
Publisher NIScPR-CSIR, India
 
Source IJFTR Vol.47(2) [June 2022]