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Comparison of four models to rank failure likelihood of individual pipes

机译：四种模型比较以对单个管道的故障可能性进行排名

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摘要

The use of statistical methods to discern patterns of historical breakage rates and use them to predict water main breaks has been widely documented. Particularly challenging is the prediction of breaks in individual pipes, due to the natural variations that exist in all the factors that affect their deterioration and subsequent failure. This paper describes alternative models developed into operational tools that can assist network owners and planners to identify individual mains for renewal in their water distribution networks. Four models were developed and compared: a heuristic model, a naive Bayesian classification model, a model based on logistic regression and finally a probabilistic model based on the non-homogeneous Poisson process (NHPP). These models rank individual water mains in terms of their anticipated breakage frequency, while considering both static (e.g. pipe material, diameter, vintage, surrounding soil, etc.) and dynamic (e.g. climate, operations, cathodic protection, etc.) effects influencing pipe deterioration rates.
机译：已经广泛地使用统计方法来识别历史破损率的模式并使用它们来预测水的主要破损。由于存在影响其劣化和后续故障的所有因素中存在的自然变化，因此预测单个管道的破裂尤其具有挑战性。本文介绍了发展为运营工具的替代模型，这些模型可以帮助网络所有者和规划者确定要在其供水网络中进行更新的各个主干。开发并比较了四个模型：启发式模型，朴素的贝叶斯分类模型，基于逻辑回归的模型以及最终基于非均匀泊松过程（NHPP）的概率模型。这些模型根据预期的破损频率对各个水管进行排名，同时考虑影响管道的静态（例如管道材料，直径，年份，周围的土壤等）和动态（例如气候，操作，阴极保护等）影响。恶化率。

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