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The Role of Artificial Neural Network Models in Ensuring the Stability of Systems

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10th International Conference on Soft Computing Models in Industrial and Environmental Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 368))

Abstract

In order to ensure smooth functioning of a production system, the stability of its processes must be guaranteed, while on the other hand it must be possible to make quick decisions encumbered with the lowest possible risk. Innovations concerning products or processes are a necessary condition to remain on the market, but they always carry the risk of losing the stability. The risk results from the uncertainty associated with making decisions as to the future, as well as from the fact that the implementation of innovations is one of the factors that disturb the current manner of the company’s operation.

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References

  1. Azadegan A, Probic L, Ghazinoory S, Samouei P (2011) Fuzzy logic in manufacturing: a review of literature and a specialized application. Int J Prod Econ 132(2)

    Google Scholar 

  2. Bubnicki Z (2005) Modern control theory. Springer, Berlin

    Google Scholar 

  3. Calvo-Rolle JL, Corchado E (2014) A bio-inspired knowledge system for improving combined cycle plant control tunin. Neurocomputing 126:95–105

    Article  Google Scholar 

  4. Krenczyk D, Dobrzanska-Danikiewicz A (2005) The deadlock protection method used in the production systems. J Mater Process Technol 164:1388–1394

    Article  Google Scholar 

  5. Krenczyk D, Skołud B (2011) Production preparation and order verification systems integration using method based on data transformation and data mapping. Lecture notes in computer science, vol. 6697, pp. 297–404

    Google Scholar 

  6. Roux O, Jamali M, Kadi D, Chatelet E (2008) Development of simulation and Optimization platform to analyse maintenance policies performance for manufacturing systems. Int J Comput Integr Manuf 21: 407–414

    Google Scholar 

  7. Vladimirs J, Vitalijs J (2012) Modelling the behaviour of stability of production systems of economics. Econ Bus 22

    Google Scholar 

  8. Wieczorek T (2008) Neuronowe modele procesów technologicznych, Monograph. Publishing House of the Silesian University of Technology, Gliwice

    Google Scholar 

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Correspondence to Anna Burduk .

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Burduk, A. (2015). The Role of Artificial Neural Network Models in Ensuring the Stability of Systems. In: Herrero, Á., Sedano, J., Baruque, B., Quintián, H., Corchado, E. (eds) 10th International Conference on Soft Computing Models in Industrial and Environmental Applications. Advances in Intelligent Systems and Computing, vol 368. Springer, Cham. https://doi.org/10.1007/978-3-319-19719-7_37

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  • DOI: https://doi.org/10.1007/978-3-319-19719-7_37

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19718-0

  • Online ISBN: 978-3-319-19719-7

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