735
Views
37
CrossRef citations to date
0
Altmetric
Research Articles

Pipeline failure prediction in water distribution networks using evolutionary polynomial regression combined with K-means clustering

, , &
Pages 737-742 | Received 18 Jan 2016, Accepted 20 Oct 2016, Published online: 22 Nov 2016

References

  • Achim, D., Ghotb, F. and McManus, K.J., 2007. Prediction of water pipe asset life using neural networks. Journal of Infrastructure Systems, 13 (1), 26–30.10.1061/(ASCE)1076-0342(2007)13:1(26)
  • Ahn, J., Lee, S., Lee, G. and Koo, J., 2005. Predicting water pipes breaks using neural network. Water Supply, 5 (3–4), 159–172.
  • Berardi, L., Kapelan, Z., Giustolisi, O. and Savic, D.A., 2008. Development of pipe deterioration models for water distribution systems using EPR. Journal of Hydroinformatics, 10 (2), 113–126.10.2166/hydro.2008.012
  • Boxall, J.B., O’Hagan, A., Pooladsaz, S., Saul, A.J., et al., 2007. Estimation of burst rates in water distribution mains. Institution of Civil Engineers Water Management, 160 (2), 73–82.10.1680/wama.2007.160.2.73
  • Clair St, A.M. and Sinha, S., 2012. State-of-the-technology review on water pipe condition, deterioration and failure rate prediction models! Urban Water Journal, 9 (2), 85–112.10.1080/1573062X.2011.644566
  • Fayyad, U., Piatetsky-Shapiro, G. and Smyth, P., 1996. From data mining to knowledge discovery in databases. Al Magazine, 17, 37–54.
  • Folkman, S., 2012. Water main break rates in the USA and Canada: A comprehensive study. Logan, UT: Utah State University, Buried Structures Laboratory.
  • Giustolisi, O. and Savic, D.A., 2006. A symbolic data-driven technique based on evolutionary polynomial regression. Journal of Hydroinformatics, 8 (3), 207–222.
  • Giustolisi, O. and Berardi, L., 2009. Prioritizing pipe replacement: From multiobjective genetic algorithms to operational decision support. Journal of Water Resources Planning and Management, 135 (6), 484–492.10.1061/(ASCE)0733-9496(2009)135:6(484)
  • Giustolisi, O. and Savic, D.A., 2009. Advances in data-driven analyses and modelling using EPR-MOGA. Journal of Hydroinformatics, 11 (3–4), 225–236.
  • Giustolisi, O., Savic, D. and Laucelli, D., 2009. Asset deterioration analysis using multi-utility data and multi-objective data mining. Journal of Hydroinformatics, 11 (3–4), 211–224.
  • Grossman R, Seni G, Elder, J, Agarwal, N., et al., 2010. Ensemble methods in data mining: Improving 522 accuracy through combining predictions. San Rafael, CA: Morgan & Claypool.
  • Jenks, G.F., 1963. Generalization in statistical mapping. Annals of the Association of American Geographers, 53 (1), 15–26.10.1111/j.1467-8306.1963.tb00429.x
  • Kabir, G., Demissie, G., Sadiq, R. and Tesfamariam, S., 2015. Integrating failure prediction models for water mains: Bayesian belief network based data fusion. Knowledge-Based Systems, 85, 159–169.
  • Kleiner, Y. and Rajani, B., 2001. Comprehensive review of structural deterioration of water mains: Statistical models. Urban Water, 3 (3), 131–150.10.1016/S1462-0758(01)00033-4
  • Kleiner, Y. and Rajani, B., 2012. Comparison of four models to rank failure likelihood of individual pipes. Journal of Hydroinformatics, 14 (3), 659–681.10.2166/hydro.2011.029
  • MacQueen, J., 1967. Some methods for classification and analysis of multivariate observations. In: Proceedings of the 5th Berkeley Symposium on Mathematical Statistics and Probability. Berkeley, CA: University of California Press, 281–297.
  • Makar, J.M., 2000. A preliminary analysis of failures in grey cast iron water pipes. Engineering Failure Analysis, 7 (1), 43–53.10.1016/S1350-6307(99)00005-9
  • Martínez-Codina, Á., Castillo, M., González-Zeas, D. and Garrote, L., 2015. Pressure as a predictor of occurrence of pipe breaks in water distribution networks. Urban Water Journal, 13 (7), 676–686.
  • Moriasi, D.N., Arnold, J.G., Van Liew, M.W., Bingner, R.L., et al., 2007. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the Asabe, 50 (3), 885–900.10.13031/2013.23153
  • Pelletier, G., Mailhot, A. and Villeneuve, J.P., 2003. Modeling water pipe breaks-three case studies. Journal of Water Resources Planning and Management, 129 (2), 115–123.10.1061/(ASCE)0733-9496(2003)129:2(115)
  • Rajani, B. and Kleiner, Y., 2001. Comprehensive review of structural deterioration of water mains: Physically based models. Urban Water, 3 (3), 151–164.10.1016/S1462-0758(01)00032-2
  • Røstum, J., 2000. Statistical modelling of pipe failures in water networks. Thesis (PhD). Norway: University of Science and Technology.
  • Sadiq, R., Rajani, B. and Kleiner, Y., 2004. Fuzzy-based method to evaluate soil corrosivity for prediction of water main deterioration. Journal of Infrastructure Systems, 10 (4), 149–156.10.1061/(ASCE)1076-0342(2004)10:4(149)
  • Scheidegger, A., Leitão, J.P. and Scholten, L., 2015. Statistical failure models for water distribution pipes – A review from a unified perspective. Water Research, 83, 237–247.10.1016/j.watres.2015.06.027
  • Tabesh, M., Soltani, J., Farmani, R. and Savic, D.A., 2009. Assessing pipe failure rate and mechanical reliability of water distribution networks using data-driven modelling. Journal of Hydroinformatics, 11 (1), 1–17.10.2166/hydro.2009.008
  • Watson, T.G., Christian, C.D., Mason, A.J., Smith, M.H. et al., 2004. Bayesian-based pipe failure model. Journal of Hydroinformatics, 6 (4), 259–264.
  • Xu, Q., Chen, Q., Li, W. and Ma, J., 2011. Pipe break prediction based on evolutionary data-driven methods with brief recorded data. Reliability Engineering and System Safety, 96 (8), 942–948.10.1016/j.ress.2011.03.010

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.