A fuzzy logic based approach to leakage forecasting in water industry

Lech Birek, Dobrila Petrovic, John Boylan

Research output: Contribution to conferencePaper


Leakage and demand forecasting is a crucial part of the resource planning decision making in the UK water industry. OFWAT - the economic regulatory body - sets the annual leakage targets for 5 years in advance. However, the leakage is not constant throughout the year and depends on the leakage control policy applied, external factors and seasonal fluctuations. The leakage for each month of the year is forecasted and later adjusted every quarter as new data become available. In this paper, a new system is developed to help the expert in adjusting the leakage forecast based on the newly available data, as well as other factors used for leakage forecasting, such as Natural Rate of Rise (relates to the rate at which the leakage increases over time), efficiency measures (hours to detect the leakage) and the number of reported and detected leakages. Fuzzy clustering and a fuzzy interpolation method are applied to generate fuzzy if-then rules based on the recorded data. The fuzzy rules represent imprecise knowledge of the relationship between the above mentioned factors and leakages. The leakage forecast is then adjusted using the generated fuzzy rules. The proposed approach is verified using real-life data from one of the leading water supply companies in the UK
Original languageEnglish
Publication statusPublished - 2011
EventThe 31st Annual International Symposium on Forecasting - Prague, Czech Republic
Duration: 26 Jun 201129 Jun 2011


ConferenceThe 31st Annual International Symposium on Forecasting
Country/TerritoryCzech Republic

Bibliographical note

This paper was given at the 31st Annual International Symposium on Forecasting, June 26-29 2011, Prague. The paper is available at: http://www.forecasters.org/submissions/BirekLechISF2011.pdf


  • leakage forecasting
  • c-means clustering
  • fuzzy logic
  • water industry


Dive into the research topics of 'A fuzzy logic based approach to leakage forecasting in water industry'. Together they form a unique fingerprint.

Cite this