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Visual Data Mining: Using Self-Organizing Maps for Electricity Distribution Regulation

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Digital Enterprise and Information Systems (DEIS 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 194))

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Abstract

The electricity distribution regulation and efficiency benchmarking practice in Finland has drawn attention because of its controversial regulatory scheme and arguably efficient electricity distribution sector. This study uses a computational intelligence tool, i.e., Self-Organizing Map (SOM), in the context of electricity distribution efficiency performance visualization. A SOMmodel has been built based on collected data for 2001-2004. It allows the reader to discriminate between the Finnish DSOs’ differing operating circumstances. Through clustering and visualization, an overall perspective of the efficiency performance of the DSOs in 2001-2004 is rendered. In addition, such a visualization approach connects the DSO’s efficiency performance to its respective operating characteristics, which is otherwise not straightforwardly indicated by only studying efficiency scores. This application provides evidence that visual data mining with the SOM as a complementary approach in electricity distribution regulation and efficiency benchmarking has the potential to be expended to other regulatory practices (e.g., yardstick regulation).

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Author information

Authors and Affiliations

  1. Turku Centre for Computer Science (TUCS), Åbo Akademi University, Joukahaisenkatu 3-5 A, 20520, Turku, Finland

    Hongyan Liu, Tomas Eklund & Barbro Back

  2. Pori School of Technology and Economics, Tampere University of Technology, Tampere, Finland

    Hannu Vanharanta

Authors
  1. Hongyan Liu
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  2. Tomas Eklund
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  3. Barbro Back
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  4. Hannu Vanharanta
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Editor information

Editors and Affiliations

  1. London Metropolitan Business School, London Metropolitan Business University, Eden grove - EG4.06, N7 8EA, London, UK

    Ezendu Ariwa

  2. Information Systems Department, King Saud University, 11543, Riyadh, Saudi Arabia

    Eyas El-Qawasmeh

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© 2011 Springer-Verlag Berlin Heidelberg

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Liu, H., Eklund, T., Back, B., Vanharanta, H. (2011). Visual Data Mining: Using Self-Organizing Maps for Electricity Distribution Regulation. In: Ariwa, E., El-Qawasmeh, E. (eds) Digital Enterprise and Information Systems. DEIS 2011. Communications in Computer and Information Science, vol 194. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22603-8_55

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  • DOI: https://doi.org/10.1007/978-3-642-22603-8_55

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22602-1

  • Online ISBN: 978-3-642-22603-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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