Analysis of Hypothetical Water Distribution Network from the Application of Three Calibration Optimization Algorithms Applying the Genetic Algorithms

9 pages•Published: September 20, 2018

Fernando Silva, Thaisa Dias Goulart and Regina Mambeli Barros

Abstract

The calibration of models applied to water distribution network systems is fundamental, as this improves the computational algorithms constructed from mathematical models. In this work from a hypothetical network, three proposed calibration algorithms were tested, (a) in terms of roughness of the model; (b) in terms of roughness and random demand and (c) in terms of random roughness and pressure directed demand. The results show few differences for the three algorithms tested, the first and third results are almost identical and slightly different from the second. However, these are basis for application in real networks, where surely the more complex algorithms can produce advantages.

Keyphrases: calibration, genetic algorithms, water distribution network structure

In: Goffredo La Loggia, Gabriele Freni, Valeria Puleo and Mauro De Marchis (editors). HIC 2018. 13th International Conference on Hydroinformatics, vol 3, pages 1962-1970.

Links:	https://easychair.org/publications/paper/kX9P
	https://doi.org/10.29007/425l

BibTeX entry

@inproceedings{HIC2018:Analysis_Hypothetical_Water_Distribution,
  author    = {Fernando Silva and Thaisa Dias Goulart and Regina Mambeli Barros},
  title     = {Analysis of Hypothetical Water Distribution Network from the Application of Three Calibration Optimization Algorithms Applying the Genetic Algorithms},
  booktitle = {HIC 2018. 13th International Conference on Hydroinformatics},
  editor    = {Goffredo La Loggia and Gabriele Freni and Valeria Puleo and Mauro De Marchis},
  series    = {EPiC Series in Engineering},
  volume    = {3},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2516-2330},
  url       = {/publications/paper/kX9P},
  doi       = {10.29007/425l},
  pages     = {1962-1970},
  year      = {2018}}

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