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International Journal of Current Microbiology and Applied Sciences (IJCMAS)
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National Academy of Agricultural Sciences (NAAS)
NAAS Score: *5.38 (2019)
[Effective from January 1, 2019]
For more details click here

ICV 2017: 100.00
Index Copernicus ICI Journals Master List 2017 - IJCMAS--ICV 2017: 100.00
For more details click here

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PRINT ISSN : 2319-7692
Online ISSN : 2319-7706
Issues : 12 per year
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Editor-in-chief: Dr.M.Prakash
Index Copernicus ICV 2017: 100.00
NAAS RATING 2018: 5.38

Int.J.Curr.Microbiol.App.Sci.2018.7(4): 3134-3143
DOI: https://doi.org/10.20546/ijcmas.2018.704.356


Applications of Artificial Neural Network in Textiles
Neha Chauhan, Nirmal Yadav and Nisha Arya
Department of Textile and Apparel Designing, I.C. College of Home Science, CCSHAU, Hisar, Haryana, India
*Corresponding author
Abstract:

An Artificial Neural Network (ANN) is an information processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. The key element of this paradigm is the novel structure of the information processing system. It is composed of a large number of highly interconnected processing elements (neurones) working in unison to solve specific problems. The artificial neural network is increasingly used as a powerful tool for many real-world problems. In Textiles and Clothing industries, it involves the interaction of a large number of variables. Because of the high degree of variability in raw materials, multistage processing and a lack of precise control on process parameters, the relation between such variables and the product properties is relied on the human knowledge but it is not possible for human being to remember all the details of the process-related data over the years. ANN has proved its usefulness for resolving many problems in textiles such as prediction of yarn properties, analysis of fabric defects, process optimization etc. The power of neural networks lies in their ability to represent complex relationships and learn them directly from the data being modelled. The ability to predict these properties accurately has become a challenge due to highly non-linear and interactive behaviour of textile materials. The prediction of properties or performance of a process in advance is required to minimize the setup cost and time. The function of ANN is not constant but can be changed dynamically.


Keywords: Artificial neural network, Element
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How to cite this article:

Neha Chauhan, Nirmal Yadav and Nisha Arya. 2018. Applications of Artificial Neural Network in Textiles.Int.J.Curr.Microbiol.App.Sci. 7(4): 3134-3143. doi: https://doi.org/10.20546/ijcmas.2018.704.356