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Technical University of Crete
Technical University of Crete
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| URI | http://purl.tuc.gr/dl/dias/078E7339-3C35-4329-A994-B2FAC9CBE623 | - |
| Identifier | https://doi.org/10.1109/CDC.1998.757868 | - |
| Identifier | http://ieeexplore.ieee.org/document/757868/?denied | - |
| Language | en | - |
| Extent | 2 pages | en |
| Title | High order neural networks to control manufacturing systems - a comparison study | en |
| Creator | Rovithakis, George A., 1968- | en |
| Creator | Gaganis Vasileios | en |
| Creator | Γαγανης Βασιλειος | el |
| Creator | Perrakis, Stelios | en |
| Creator | Christodoulou Manolis | en |
| Creator | Χριστοδουλου Μανωλης | el |
| Publisher | Institute of Electrical and Electronics Engineers | en |
| Content Summary | In this paper the neuro adaptive scheduling methodology is evaluated by comparing its performance with conventional schedulers, through simulation studies. The case study chosen constitutes an existing manufacturing cell, which can be viewed as a highly complex nonacyclic FMS, with extremely heterogenous part processing times. The results reveal superiority of our algorithm in terms of backlogging and inventory cost, system stability and work-in-process | en |
| Type of Item | Πλήρης Δημοσίευση σε Συνέδριο | el |
| Type of Item | Conference Full Paper | en |
| License | http://creativecommons.org/licenses/by/4.0/ | en |
| Date of Item | 2015-11-07 | - |
| Date of Publication | 1998 | - |
| Subject | Artificial neural networks | en |
| Subject | Nets, Neural (Computer science) | en |
| Subject | Networks, Neural (Computer science) | en |
| Subject | Neural nets (Computer science) | en |
| Subject | neural networks computer science | en |
| Subject | artificial neural networks | en |
| Subject | nets neural computer science | en |
| Subject | networks neural computer science | en |
| Subject | neural nets computer science | en |
| Bibliographic Citation | G. Rovithakis, V. Gaganis, S. Perrakis and M. Christodoulou, “High order neural networks to control manufacturing systems - a comparison study”, in 37th IEEE Conference on Decision and Control, 1998, pp. 2736-2737. doi: 10.1109/CDC.1998.757868 | en |
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