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Recurrent Neural Networks for Industrial Procurement Decisions

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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.

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Authors and Affiliations

  1. Corporate Technology, Intelligent Systems and Control (CT T IAT ISC), Siemens AG, Otto-Hahn-Ring 6, 81739, Munich, Germany

    Hans-Georg Zimmermann, Christoph Tietz, Ralph Grothmann & Thomas Runkler

Authors
  1. Hans-Georg Zimmermann
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  2. Christoph Tietz
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  3. Ralph Grothmann
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  4. Thomas Runkler
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Corresponding author

Correspondence to Thomas Runkler.

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Zimmermann, HG., Tietz, C., Grothmann, R. et al. Recurrent Neural Networks for Industrial Procurement Decisions. Künstl Intell 26, 403–406 (2012). https://doi.org/10.1007/s13218-012-0194-3

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  • DOI: https://doi.org/10.1007/s13218-012-0194-3

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