Practical Approach to Prediction of Plant Technological Parameters with Missing Data

  • Marián Hrehuš
  • Štefan Figedy
Conference paper
Part of the Advances in Soft Computing book series (AINSC, volume 5)


The novel approach how to determine the past and future time horizon for prediction of plant technological parameters with missing data is described. These situations frequently happen in real life when the whole spans of time data are missing due to e.g. plant outages. For this, the mutual information analysis has been proposed to use. The hierarchical training of ANNs has been applied to reduce the error of time series forecasting.


Mutual Information Time Horizon Time Series Forecast Chaotic Time Series Predictive Maintenance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Marián Hrehuš
    • 1
  • Štefan Figedy
    • 1
  1. 1.VÚJE TrnavaTrnavaSlovak Rep.

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