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Harmonisation of Soft Logical Inference Rules in Distributed Decision Systems

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Knowledge-Based Intelligent Information and Engineering Systems (KES 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4252))

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Abstract

It is considered a problem of harmonisation of diagnostic rules used in a distributed set of diagnostic centres, the rules being based on a k-most-similar-cases approach. Harmonisation is reached due to an exchange of diagnostic cases among the reference sets stored in the centres. The method is based on general concepts of similarity, semi-similarity and structural compatibilitymeasures used to evaluation of adequacy of records in remote data files to the requirements connected with supporting decision making in a given, local diagnostic centre. The procedure of local reference set extension by diagnostic cases selection and acquisition is described.

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Author information

Authors and Affiliations

  1. Institute of Biocybernetics and Biomedical Engineering PAS, Warsaw, Poland

    Juliusz L. Kulikowski

Authors
  1. Juliusz L. Kulikowski
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Editors and Affiliations

  1. School of Design, Engineering and Computing, Bournemouth University, UK

    Bogdan Gabrys

  2. Centre for SMART Systems, School of Environment and Technology, University of Brighton, BN2 4GJ, Brighton, UK

    Robert J. Howlett

  3. School of Electrical and Information Engineering, Knowledge Based Intelligent Engineering Systems Centre, University of South Australia, SA, 5095, Mawson Lakes, Australia

    Lakhmi C. Jain

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© 2006 Springer-Verlag Berlin Heidelberg

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Kulikowski, J.L. (2006). Harmonisation of Soft Logical Inference Rules in Distributed Decision Systems. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2006. Lecture Notes in Computer Science(), vol 4252. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893004_30

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  • DOI: https://doi.org/10.1007/11893004_30

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-46537-9

  • Online ISBN: 978-3-540-46539-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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