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A Soft Sensor Model Based on Rough Set Theory and Its Application in Estimation of Oxygen Concentration

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Fuzzy Systems and Knowledge Discovery (FSKD 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3613))

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Abstract

At present, much more research in the field of soft sensor modeling is concerned. In the process of establishing soft sensor models, how to select the secondary variables is still an unresolved question. In this paper, rough set theory is used to select the secondary variables from the initial sample data. This method is used to build the soft sensor model to estimate the oxygen concentration in a regeneration tower and the good result is obtained.

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Author information

Authors and Affiliations

  1. Research Institute of Automation, East China University of Science & Technology, Shanghai, 200237, P. R. China

    Xingsheng Gu & Dazhong Sun

Authors
  1. Xingsheng Gu
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  2. Dazhong Sun
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Editor information

Editors and Affiliations

  1. School of Electrical and Electronic Engineering, Nanyang Technological University, Block S1, Nanyang Avenue, 639798, Singapore

    Lipo Wang

  2. Honda Research Institute Europe GmbH, Offenbach/Main, Germany

    Yaochu Jin

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© 2005 Springer-Verlag Berlin Heidelberg

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Gu, X., Sun, D. (2005). A Soft Sensor Model Based on Rough Set Theory and Its Application in Estimation of Oxygen Concentration. In: Wang, L., Jin, Y. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2005. Lecture Notes in Computer Science(), vol 3613. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539506_160

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  • DOI: https://doi.org/10.1007/11539506_160

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28312-6

  • Online ISBN: 978-3-540-31830-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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