Soft Computing Approaches for Urban Water Demand Forecasting

  • Konstantinos Kokkinos
  • Elpiniki I. PapageorgiouEmail author
  • Katarzyna Poczeta
  • Lefteris Papadopoulos
  • Chrysi Laspidou
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 57)


This paper presents an integrated framework for water resources management at urban level which consists of a Neuro-Fuzzy and Fuzzy Cognitive Map-based, (FCM) decision support system (DSS) based on multiple objectives and multiple disciplines for planning and forecasting. The proposed DSS has as primary goals to: (a) adaptively control the water pressure of the water distribution system by forecasting the water demand at the urban level and (b) to reduce leakage of the water network by controlling the water pressure. The system follows a model-driven architecture with the inclusion of the FCM-based models and a spatio-temporal model for arranging all data. The validation of the proposed learning algorithms is made for two case studies that comprise different water supply characteristics and correspond to different locations in Europe.


Fuzzy Cognitive Maps Neuro-Fuzzy Water management Forecasting Prediction Decision support 


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Authors and Affiliations

  • Konstantinos Kokkinos
    • 1
  • Elpiniki I. Papageorgiou
    • 2
    • 3
    Email author
  • Katarzyna Poczeta
    • 4
  • Lefteris Papadopoulos
    • 1
  • Chrysi Laspidou
    • 5
  1. 1.Information Technologies InstituteThermiGreece
  2. 2.Department of Computer EngineeringTechnological Education Institute/University of Applied Sciences of Central GreeceLamiaGreece
  3. 3.Faculty of Business EconomicsHasselt UniversityHasseltBelgium
  4. 4.Department of Information SystemsKielce University of TechnologyKielcePoland
  5. 5.Department of Civil EngineeringUniversity of ThessalyNea IoniaGreece

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