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http://nopr.niscpr.res.in/handle/123456789/4330Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Tanikic, Dejan | - |
| dc.contributor.author | Manic, Miodrag | - |
| dc.contributor.author | Radenkovic, Goran | - |
| dc.contributor.author | Mancic, Dragan | - |
| dc.date.accessioned | 2009-05-26T12:31:23Z | - |
| dc.date.available | 2009-05-26T12:31:23Z | - |
| dc.date.issued | 2009-06 | - |
| dc.identifier.issn | 0022-4456 | - |
| dc.identifier.uri | http://hdl.handle.net/123456789/4330 | - |
| dc.description | 530-539 | en_US |
| dc.description.abstract | This study presents metal cutting process’ parameters modeling (cutting temperature, cutting force, and quality of machinedsurface) using artificial neural networks, and hybrid, adaptive neuro-fuzzy systems. Proposed models can be used for metalcutting process optimization, increasing productivity and reducing manufacturing costs. | en_US |
| dc.language.iso | en_US | en_US |
| dc.publisher | CSIR | en_US |
| dc.source | JSIR Vol.68(06) [June 2009] | en_US |
| dc.subject | Artificial neural networks | en_US |
| dc.subject | Metal cutting process | en_US |
| dc.subject | Neuro-fuzzy system | en_US |
| dc.title | Metal cutting process parameters modeling: an artificial intelligence approach | en_US |
| dc.type | Article | en_US |
| Appears in Collections: | JSIR Vol.68(06) [June 2009] | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| JSIR 68(6) 530-539.pdf | 199.95 kB | Adobe PDF | View/Open |
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