Using Self-organizing Map in a Computerized Decision Support System

  • Miki Sirola
  • Golan Lampi
  • Jukka Parviainen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3316)


Modern computerized decision support systems have developed to their current status during many decades. The variety of methodologies and application areas has increased during this development. In this paper neural method Self-Organizing Map (SOM) is combined with knowledge-based methodologies in a rule-based decision support system prototype. This system, which may be applied for instance in fault diagnosis, is based on an earlier study including compatibility analysis. A Matlab-based tool can be used for example in fault detection and identification. We show with an example how SOM analysis can help decision making in a computerized decision support system. An error state model made in Simulink programming environment is used to produce data for the analysis. Quantisation error between normal data and error data is one significant tool in the analysis. This kind of decision making is necessary for instance in state monitoring in control room of a safety critical process in industry.


Decision Support System Quantisation Error Computerize Decision Support System Compatibility Analysis Base Decision Support System 
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 2004

Authors and Affiliations

  • Miki Sirola
    • 1
  • Golan Lampi
    • 1
  • Jukka Parviainen
    • 1
  1. 1.Laboratory of Computer and Information ScienceHelsinki University of TechnologyFinland

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