Please use this identifier to cite or link to this item: http://nopr.niscair.res.in/handle/123456789/8573
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dc.contributor.authorDhas, J Edwin Raja-
dc.contributor.authorKumanan, Somasundaram-
dc.date.accessioned2010-04-29T06:20:44Z-
dc.date.available2010-04-29T06:20:44Z-
dc.date.issued2010-05-
dc.identifier.issn0975-1084 (Online); 0022-4456 (Print)-
dc.identifier.urihttp://hdl.handle.net/123456789/8573-
dc.description350-355en_US
dc.description.abstractThis paper presents development of neuro hybrid model (NHM) to predict weld bead width in submerged arc welding.Experiments were designed using Taguchi’s principles and results were used to develop a multiple regression model. Data setgenerated from Multiple Regression Analysis (MRA) was utilized in ANN model, which was trained with backpropagation algorithm in MATLAB platform and used to develop NHM to predict quality of weld. NHM is flexible and accurate than existing models for a better online monitoring system.en_US
dc.language.isoen_USen_US
dc.publisherCSIRen_US
dc.sourceJSIR Vol.69(05) [May 2010]en_US
dc.subjectBead widthen_US
dc.subjectHybrid neuro modelen_US
dc.subjectMultiple regression modelen_US
dc.subjectSubmerged arc weldingen_US
dc.titleNeuro hybrid model to predict weld bead width in submerged arcwelding processen_US
dc.typeArticleen_US
Appears in Collections:JSIR Vol.69(05) [May 2010]

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