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http://nopr.niscpr.res.in/handle/123456789/8573Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Dhas, J Edwin Raja | - |
| dc.contributor.author | Kumanan, Somasundaram | - |
| dc.date.accessioned | 2010-04-29T06:20:44Z | - |
| dc.date.available | 2010-04-29T06:20:44Z | - |
| dc.date.issued | 2010-05 | - |
| dc.identifier.issn | 0975-1084 (Online); 0022-4456 (Print) | - |
| dc.identifier.uri | http://hdl.handle.net/123456789/8573 | - |
| dc.description | 350-355 | en_US |
| dc.description.abstract | This 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.iso | en_US | en_US |
| dc.publisher | CSIR | en_US |
| dc.source | JSIR Vol.69(05) [May 2010] | en_US |
| dc.subject | Bead width | en_US |
| dc.subject | Hybrid neuro model | en_US |
| dc.subject | Multiple regression model | en_US |
| dc.subject | Submerged arc welding | en_US |
| dc.title | Neuro hybrid model to predict weld bead width in submerged arcwelding process | en_US |
| dc.type | Article | en_US |
| Appears in Collections: | JSIR Vol.69(05) [May 2010] | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| JSIR 69(5) 350-355.pdf | 123.04 kB | Adobe PDF | View/Open |
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