Please use this identifier to cite or link to this item: http://nopr.niscpr.res.in/handle/123456789/54576
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dc.contributor.authorHeydarian, Parisa-
dc.contributor.authorVadood, Morteza-
dc.contributor.authorYazdi, Ali Asghar Alamdar-
dc.date.accessioned2020-06-23T06:23:16Z-
dc.date.available2020-06-23T06:23:16Z-
dc.date.issued2020-06-
dc.identifier.issn0975-1025 (Online); 0971-0426 (Print)-
dc.identifier.urihttp://nopr.niscair.res.in/handle/123456789/54576-
dc.description220-223en_US
dc.description.abstractPresented study is aimed at designing a model for bending length based on the concentrated loading method using 10 parameters extracted from the modified tensile test. After that, a new database has been reproduced by using principal component analysis and the modeling is conducted by regression and artificial neural network (ANN) based on the trial and error method. The obtained R-squared of 0.97 between ANN outputs and corresponding real bending lengths proves that the proposed method has a great potential for evaluating the mechanical properties of fabrics.en_US
dc.language.isoen_USen_US
dc.publisherNISCAIR-CSIR, Indiaen_US
dc.rights CC Attribution-Noncommercial-No Derivative Works 2.5 Indiaen_US
dc.sourceIJFTR Vol.45(2) [June 2020]en_US
dc.subjectArtificial neural networken_US
dc.subjectBending lengthen_US
dc.subjectConcentrated loading methoden_US
dc.subjectPolypropyleneen_US
dc.subjectPrincipal component analysisen_US
dc.titleModeling of bending length based on concentrated loading methoden_US
dc.typeArticleen_US
Appears in Collections:IJFTR Vol.45(2) [June 2020]

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