References

Achim, D., F. Ghotb and K.J. McManus, 2007. Prediction of water pipe asset life using neural networks. J. Infrastruct. Syst., 13: 26-30.
Direct Link  |  

Al-Barqawi, H. and T. Zayed, 2006. Condition rating model for underground infrastructure sustainable water mains. J. Perform. Constr. Facil., 20: 126-135.
Direct Link  |  

Andreou, S.A., D.H. Marks and R.M. Clark, 1987. A new methodology for modelling break failure patterns in deteriorating water distribution systems: Applications. Adva. Water Resour., 10: 11-20.
Direct Link  |  

Babovic, V., J.P. Drecourt, M. Keijzer and P.F. Hansen, 2002. A data mining approach to modelling of water supply assets. Urban Water, 4: 401-414.
Direct Link  |  

Ben-Gal, I., F. Ruggeri, F. Faltin and R. Kenett, 2007. Bayesian Networks. In: Encyclopedia of Statistics in Quality and Reliability, Fabrizio R. (Ed.). Wiley, Hoboken, New Jersey, USA., pp: 1-6.

Buttrick, D.B., A.V. Schalkwyk, R.J. Kleywegt, R.B. Watermeyer and N. Trollip, 2002. Proposed method for dolomite land hazard and risk assessment in South Africa. J. S. Afr. Inst. Civil Eng., 44: 27-36.
Direct Link  |  

Christodoulou, S., A. Deligianni, P. Aslani and A. Agathokleous, 2009. Risk-based asset management of water piping networks using neurofuzzy systems. Comput. Environ. Urban Syst., 33: 138-149.
Direct Link  |  

Christodoulou, S., P. Aslani and A. Vanrenterghem, 2003. A risk analysis framework for evaluating structural degradation of water mains in urban settings, using neurofuzzy systems and statistical modeling techniques. Proceedings of the Congress on World Water and Environmental Resources, June 23-26, 2003, American Society of Civil Engineers, Pennsylvania, USA., pp: 1-9.

Clair, S.A.M. and S. Sinha, 2012. State-of-the-technology review on water pipe condition, deterioration and failure rate prediction models!. Urban Water J., 9: 85-112.
Direct Link  |  

Colombo, A.F., P. Lee and B.W. Karney, 2009. A selective literature review of transient-based leak detection methods. J. Hydro Environ. Res., 2: 212-227.
Direct Link  |  

Davis, P., D.D. Silva, D. Marlow, M. Moglia and S. Gould et al., 2008. Failure prediction and optimal scheduling of replacements in asbestos cement water pipes. J. Water Supply Res. Technol. Aqua, 57: 239-252.
CrossRef  |  Direct Link  |  

Davis, P., S. Burn and S. Gould, 2008. Fracture prediction in tough polyethylene pipes using measured craze strength. Polym. Eng. Sci., 48: 843-852.
CrossRef  |  Direct Link  |  

Davis, P., S. Burn, M. Moglia and S. Gould, 2007. A physical probabilistic model to predict failure rates in buried PVC pipelines. Reliab. Eng. Syst. Saf., 92: 1258-1266.
Direct Link  |  

Dehghan, A., K.J. McManus and E.F. Gad, 2008. Probabilistic failure prediction for deteriorating pipelines: Nonparametric approach. J. Perform. Constr. Facil., 22: 45-53.
Direct Link  |  

Dehghan, A., K.J. McManus and E.F. Gad, 2008. Statistical analysis of structural failures of water pipes. Proceedings of the Conference on Institution of Civil Engineers-Water Management Vol. 161, August 25-27 2008, Thomas Telford Ltd, London, England, pp: 207-214.

Doguc, O. and J.E. Ramirez-Marquez, 2009. A generic method for estimating system reliability using Bayesian networks. Reliab. Eng. Syst. Saf., 94: 542-550.
CrossRef  |  Direct Link  |  

Engelhardt, M.O., P.J. Skipworth, D.A. Savic, A.J. Saul and G.A. Walters, 2000. Rehabilitation strategies for water distribution networks: A literature review with a UK perspective. Urban Water, 2: 153-170.
Direct Link  |  

Fares, H. and T. Zayed, 2010. Hierarchical fuzzy expert system for risk of failure of water mains. J. Pipeline Syst. Eng. Pract., 1: 53-62.
Direct Link  |  

Fenton, N., P. Krause and M. Neil, 2002. Software measurement: Uncertainty and causal modeling. IEEE. Software, 19: 116-122.
CrossRef  |  Direct Link  |  

Francis, R.A., S.D. Guikema and L. Henneman, 2014. Bayesian belief networks for predicting drinking water distribution system pipe breaks. Reliab. Eng. Syst. Saf., 130: 1-11.
Direct Link  |  

Gat, L.Y. and P. Eisenbeis, 2000. Using maintenance records to forecast failures in water networks. Urban Water, 2: 173-181.
Direct Link  |  

Heckerman, D. 1996. Bayesian Networks for Knowledge Discovery. In: Advances in Knowledge Discovery and Data Mining, Fayyad, U., G. Piatetsky-Shapiro, P. Smith and R. Urthurusamy (Eds.). Chapter-11, AAAI Press/The MIT Press, ISBN:0-262-56097-6, pp: 273-306.

Kabir, G., R. Sadiq and S. Tesfamariam, 2016. A fuzzy Bayesian belief network for safety assessment of oil and gas pipelines. Struct. Infrastruct. Eng., 12: 874-889.
Direct Link  |  

Kabir, G., S. Tesfamariam, A. Francisque and R. Sadiq, 2015. Evaluating risk of water mains failure using a Bayesian belief network model. Eur. J. Oper. Res., 240: 220-234.
Direct Link  |  

Kleiner, Y. and B. Rajani, 1999. Using limited data to assess future needs. Am. Water Works Assoc. J., 91: 47-62.
Direct Link  |  

Kleiner, Y. and B. Rajani, 2000. Considering time-dependent factors in the statistical prediction of water main breaks. Proceedings of the Conference on American Water Works Association Infrastructure, March 12-15, 2000, Baltimore, National Research Council, Maryland, pp: 1-12.

Kleiner, Y. and B. Rajani, 2001. Comprehensive review of structural deterioration of water mains: Statistical models. Urban Water, 3: 131-150.
Direct Link  |  

Mailhot, A., A. Poulin and J.P. Villeneuve, 2003. Optimal replacement of water pipes. Water Resour. Res., Vol. 39, 10.1029/2002WR001904

Makar, J.M. and Y. Kleiner, 2000. Maintaining water pipeline integrity. Proceedings of the Conference and Exhibition on AWWA Infrastructure, March 12-15, 2000, Baltimore, Maryland, Institute for Research in Construction, pp: 1-13.

Margaritis, D., 2003. Learning Bayesian network model structure from data. Ph.D Thesis, Carnegie Mellon University, Pittsburgh, Pennsylvania.

Poulakis, Z., D. Valougeorgis and C. Papadimitriou, 2003. Leakage detection in water pipe networks using a Bayesian probabilistic framework. Probab. Eng. Mech., 18: 315-327.
Direct Link  |  

Rajani, B. and S. Tesfamariam, 2005. Estimating time to failure of ageing cast iron water mains under uncertainties. Masters Thesis, University of Exeter, Exeter, England.

Rajani, B. and S. Tesfamariam, 2007. Estimating time to failure of cast-iron water mains. Proceedings of the Conference on Water Management Vol. 160, June 14-16, 2007, Thomas Telford Ltd, London, England, pp: 83-88.

Rajani, B. and Y. Kleiner, 2001. Comprehensive review of structural deterioration of water mains: Physically based models. Urban Water, 3: 151-164.
Direct Link  |  

Savic, D.A., 2009. The Use of Data-Driven Methodologies for Prediction of Water and Wastewater Asset Failures. In: Risk Management of Water Supply and Sanitation Systems, Hlavinek, P., C. Popovska, J. Marsalek, I. Mahrikova and T. Kukharchyk (Eds.). Springer, Berlin, Germany, pp: 181.

Silva, D.D., M. Moglia, P. Davis and S. Burn, 2006. Condition assessment to estimate failure rates in buried metallic pipelines. J. Water Supply Res. Technol. Aqua, 55: 179-191.
Direct Link  |  

Stone, S.L., E.J. Dzuray, D. Meisegeier, A. Dahlborg and M. Erickson et al., 2002. Decision-support tools for predicting the performance of water distribution and wastewater collection systems. US Environmental Protection Agency, Cincinnati, Ohio.

Tabesh, M., J. Soltani, R. Farmani and D. Savic, 2009. Assessing pipe failure rate and mechanical reliability of water distribution networks using data-driven modeling. J. Hydroinf., 11: 1-17.
CrossRef  |  Direct Link  |  

Tesfamariam, S., B. Rajani and R. Sadiq, 2006. Possibilistic approach for consideration of uncertainties to estimate structural capacity of ageing cast iron water mains. Can. J. Civil Eng., 33: 1050-1064.
Direct Link  |  

Wang, C.W., Z.G. Niu, H. Jia and H.W. Zhang, 2010. An assessment model of water pipe condition using Bayesian inference. J. Zhejiang Univ. Sci. A., 11: 495-504.
CrossRef  |  Direct Link  |  

Wang, Y., T. Zayed and O. Moselhi, 2009. Prediction models for annual break rates of water mains. J. Perform. Const. Facil., 23: 47-54.
Direct Link  |  

Xu, Q., Q. Chen, J. Ma and K. Blanckaert, 2013. Optimal pipe replacement strategy based on break rate prediction through genetic programming for water distribution network. J. Hydro Environ. Res., 7: 134-140.
Direct Link  |  

Xu, Q., Q. Chen, W. Li and J. Ma, 2011. Pipe break prediction based on evolutionary data-driven methods with brief recorded data. Reliab. Eng. Syst. Saf., 96: 942-948.
Direct Link  |  

Yamijala, S., 2007. Statistical estimation of water distribution system pipe break risk. Masters Thesis, Texas A&M University, Texas, USA.