NDLI: Comparison of regression and adaptive neuro-fuzzy models for predicting the compressed air consumption in air-jet weaving

Content Provider	Springer Nature Link
Author	Hussain, Tanveer Jabbar, Abdul Ahmed, Shakeel
Copyright Year	2014
Abstract	The aim of this study was to compare the response surface regression and adaptive neuro-fuzzy models for predicting the compressed air consumption in air jet weaving. The prediction models are based on the experimental data of 100 samples comprising weft yarn count, fabric width, loom speed and reed count as input variables and compressed air consumption as output/response variable. The models quantitatively characterize the linear and quadratic relationships as well as interactions between the input and output variables exhibiting very good prediction ability and accuracy, with ANFIS model being slightly better in performance than the regression model. The models could be used for estimating the compressed air consumption, identifying air leakages and production planning in a weaving mill.
Starting Page	390
Ending Page	395
Page Count	6
File Format	PDF
ISSN	12299197
Journal	Fibers and Polymers
Volume Number	15
Issue Number	2
e-ISSN	18750052
Language	English
Publisher	The Korean Fiber Society
Publisher Date	2014-02-22
Publisher Place	Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Air-jet weaving Compressed air Prediction Regression ANFIS Polymer Sciences
Content Type	Text
Resource Type	Article
Subject	Chemistry Chemical Engineering Polymers and Plastics

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Comparison of regression and adaptive neuro-fuzzy models for predicting the compressed air consumption in air-jet weaving