Drinking Water Distribution Systems Asset Management: Statistical Modelling of Pipe Breaks
暂无分享，去创建一个
[1] Seth D. Guikema,et al. Bayesian Belief Networks for predicting drinking water distribution system pipe breaks , 2014, Reliab. Eng. Syst. Saf..
[2] Roshanak Nateghi,et al. Power Outage Estimation for Tropical Cyclones: Improved Accuracy with Simpler Models , 2014, Risk analysis : an official publication of the Society for Risk Analysis.
[3] Julie E Shortridge,et al. Public health and pipe breaks in water distribution systems: analysis with internet search volume as a proxy. , 2014, Water research.
[4] Haibo He,et al. Learning from Imbalanced Data , 2009, IEEE Transactions on Knowledge and Data Engineering.
[5] Seth D. Guikema,et al. Statistical models for the analysis of water distribution system pipe break data , 2009, Reliab. Eng. Syst. Saf..
[6] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[7] J. Friedman. Greedy function approximation: A gradient boosting machine. , 2001 .
[8] G. Pelletier,et al. Modeling the evolution of the structural state of water pipe networks with brief recorded pipe break histories: Methodology and application , 2000 .
[9] B Rajani,et al. Pipesoil interaction analysis of jointed water mains , 1996 .
[10] J. C. Jofriet. Discussion: Concrete water tanks in Ontario , 1986 .
[11] Stefanos Alexander Andreou. Predictive models for pipe break failures and their implications on maintenance planning strategies for deteriorating water distribution systems , 1986 .