| dc.contributor.author | Zimmermann, Hans-Georg | |
| dc.contributor.author | Tietz, Christoph | |
| dc.contributor.author | Grothmann, Ralph | |
| dc.contributor.author | Runkler, Thomas | |
| dc.date | 2012-11-01 | |
| dc.date.accessioned | 2018-01-08T09:16:10Z | |
| dc.date.available | 2018-01-08T09:16:10Z | |
| dc.date.issued | 2012 | |
| dc.identifier.issn | 1610-1987 | |
| dc.identifier.uri | http://dl.gi.de/handle/20.500.12116/11325 | |
| dc.description.abstract | Rational decisions are based upon forecasts. Precise forecasting has therefore a central role in business. The prediction of commodity prices or the prediction of energy load curves are prime examples. We introduce recurrent neural networks to model economic or industrial dynamic systems. | |
| dc.publisher | Springer | |
| dc.relation.ispartof | KI - Künstliche Intelligenz: Vol. 26, No. 4 | |
| dc.relation.ispartofseries | KI - Künstliche Intelligenz | |
| dc.subject | Forecasting | |
| dc.subject | Neural networks | |
| dc.title | Recurrent Neural Networks for Industrial Procurement Decisions | |
| dc.type | Text/Journal Article | |
| mci.reference.pages | 403-406 | |
| gi.identifier.doi | 10.1007/s13218-012-0194-3 | |
