Development of pipe deterioration models for water distribution systems using EPR

Created by W.Langdon from gp-bibliography.bib Revision:1.4472

  author =       "L. Berardi and Z. Kapelan and O. Giustolisi and 
                 D. A. Savic",
  title =        "Development of pipe deterioration models for water
                 distribution systems using EPR",
  journal =      "Journal of Hydroinformatics",
  year =         "2008",
  volume =       "10",
  number =       "2",
  pages =        "113--126",
  keywords =     "genetic algorithms, genetic programming, data-driven
                 modelling, evolutionary polynomial regression, failure
                 analysis, performance indicators, water systems",
  ISSN =         "1464-7141",
  URL =          "",
  DOI =          "doi:10.2166/hydro.2008.012",
  size =         "14 pages",
  abstract =     "The economic and social costs of pipe failures in
                 water and wastewater systems are increasing, putting
                 pressure on utility managers to develop annual
                 replacement plans for critical pipes that balance
                 investment with expected benefits in a risk-based
                 management context. In addition to the need for a
                 strategy for solving such a multi-objective problem,
                 analysts and water system managers need reliable and
                 robust failure models for assessing network
                 performance. In particular, they are interested in
                 assessing a conduit's propensity to fail and how to
                 assign criticality to an individual pipe segment. pipe
                 deterioration is modelled using Evolutionary Polynomial
                 Regression. This data-driven technique yields symbolic
                 formulae that are intuitive and easily understandable
                 by practitioners. The case study involves a water
                 quality zone within a distribution system and entails
                 the collection of historical data to develop network
                 performance indicators. Finally, an approach for
                 incorporating such indicators into a decision support
                 system for pipe rehabilitation/replacement planning is
                 introduced and articulated.",
  notes =        "Fig 5 bathtub curve

                 Hydroinformatics Group, Technical University of Bari,
                 via Orabona 4, I-70125, Bari, Italy",

Genetic Programming entries for Luigi Berardi Zoran Kapelan Orazio Giustolisi Dragan Savic