A Multiple-Layer Clustering Method for Real-Time Decision Support in a Water Distribution System

  • Alexandru Predescu
  • Cătălin Negru
  • Mariana MocanuEmail author
  • Ciprian Lupu
  • Antonio Candelieri
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 339)


Machine learning provides a foundation for a new paradigm where the facilities of computing extend to the level of cognitive abilities in the form of decision support systems. In the area of water distribution systems, there is an increased demand in data processing capabilities as smart meters are being installed providing large amounts of data. In this paper, a method for multiple-layer data processing is defined for prioritizing pipe replacements in a water distribution system. The identified patterns provide relevant information for calculating the associated priorities as part of a real-time decision support system. A modular architecture provides insights at different levels and can be extended to form a network of networks. The proposed clustering method is compared to a single clustering of aggregated data in terms of the overall accuracy.


Decision support system Machine learning Multiple-layer clustering 



We are thankful to the PN III Program P3 - European and International Cooperation, UEFISCDI, that supported the research activity and part of the presentation in conference, as well as to the H2020 Twinning Program, that partially supported the publication under the 690900 project - Data4Water


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Alexandru Predescu
    • 1
  • Cătălin Negru
    • 1
  • Mariana Mocanu
    • 1
    Email author
  • Ciprian Lupu
    • 1
  • Antonio Candelieri
    • 2
  1. 1.Department of Computer ScienceUniversity POLITEHNICA of BucharestBucharestRomania
  2. 2.Department of Computer ScienceUniversity of Milano BicoccaMilanItaly

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