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Gating Artificial Neural Network Based Soft Sensor

  • Petr Kadlec
  • Bogdan Gabrys
Part of the Studies in Computational Intelligence book series (SCI, volume 134)

Abstract

This work proposes a novel approach to Soft Sensor modelling, where the Soft Sensor is built by a set of experts which are artificial neural networks with randomly generated topology. For each of the experts a meta neural network is trained, the gating Artificial Neural Network. The role of the gating network is to learn the performance of the experts in dependency on the input data samples. The final prediction of the Soft Sensor is a weighted sum of the individual experts predictions. The proposed meta-learning method is evaluated on two different process industry data sets.

Keywords

Hide Unit Soft Sensor Correlation Base Feature Selection Principle Component Regression Gating Network 
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 2008

Authors and Affiliations

  • Petr Kadlec
    • 1
  • Bogdan Gabrys
    • 1
  1. 1.Computational Intelligence Research GroupBournemouth University Fern Barrow, PooleUnited Kingdom

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