Pipe failure prediction models are essential for informing proactive management decisions. This study aims to establish a reliable prediction model returning the probability of pipe failure using a gradient boosted tree model, and a specific segmentation and grouping of pipes on a 1 km grid that associates localised characteristics. The model is applied to an extensive UK network with approximately 40,000 km of pipeline and a 14-year failure history. The model was evaluated using the Receiver Operator Curve and Area Under the Curve (0.89), briers score (0.007) and Mathews Correlation Coefficient (0.27) for accuracy, indicating acceptable predictions. A weighted risk analysis is used to identify the consequence of a pipe failure and provide a graphical representation of high-risk pipes for decision makers. The weighted risk analysis provided an important step to understanding the consequences of the predicted failure. The model can be used directly in strategic planning, which sets long-term key decisions regarding maintenance and potential replacement of pipes.

管道故障预测模型对于通知主动管理决策至关重要。本研究旨在建立一个可靠的预测模型，使用梯度提升树模型返回管道故障概率，并在 1 公里网格上对管道进行特定的分割和分组，以关联局部特征。该模型适用于拥有约 40,000 公里管道和 14 年故障历史的广泛英国网络。使用接收器算子曲线和曲线下面积 (0.89)、briers 分数 (0.007) 和 Mathews 相关系数 (0.27) 评估模型的准确性，表明可以接受的预测。加权风险分析用于识别管道故障的后果，并为决策者提供高风险管道的图形表示。加权风险分析为理解预测故障的后果提供了一个重要步骤。该模型可直接用于战略规划，制定有关维护和潜在更换管道的长期关键决策。