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首页> 外文期刊>Journal of Infrastructure Systems >Infrastructure Management: Integrated Ahp/ann Model To Evaluate Municipal Water Mains' Performance
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Infrastructure Management: Integrated Ahp/ann Model To Evaluate Municipal Water Mains' Performance

机译：基础设施管理：集成的Ahp / ann模型评估市政供水主管的绩效

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摘要

Canadian municipalities have noted that 59% of their water systems needed repair and the status of 43% of these systems is unacceptable. In the United States, ASCE assigned a near failing grade of D- to the condition of water system infrastructure. Therefore, municipalities face a great challenge of managing the expected large replacement and new installation projects of water mains. This research aims at designing a robust model in order to assess the condition and predict the performance of water mains. Data are collected from three different Canadian municipalities: (1) Moncton (New Brunswick); (2) London (Ontario); and (3) Longueiul (Quebec). An integrated model and framework, using an analytic hierarchy process (AHP) and artificial neural network (ANN), are developed. In addition, an automated, user-friendly, web-based infrastructure management tool (CR-Predictor) is developed based on the integrated AHP/ANN model to assess water main condition. The developed tool and models are validated in which they show robust results (98.51%)-the average validity percent. They are expected to benefit academics and practitioners (municipal engineers, consultants, and contractors) to prioritize inspection and rehabilitation planning for existing water mains.
机译：加拿大市政当局指出，他们的供水系统中有59％需要维修，而这些系统中有43％的状况是不可接受的。在美国，ASCE将D-等级评定为接近水系统基础设施状况。因此，市政当局面临着管理预期的大型水管更换和新安装项目的巨大挑战。本研究旨在设计一个鲁棒的模型，以评估状况并预测水管的性能。数据收集自加拿大三个不同的城市：（1）蒙克顿（新不伦瑞克省）； （2）伦敦（安大略省）； （3）Longueiul（魁北克）。开发了使用层次分析法（AHP）和人工神经网络（ANN）的集成模型和框架。此外，基于集成的AHP / ANN模型，开发了一种自动化，用户友好的基于Web的基础设施管理工具（CR-Predictor），用于评估水的主要状况。所开发的工具和模型经过验证，可以显示出可靠的结果（98.51％）-平均有效性百分比。预计它们将使学者和从业人员（市政工程师，顾问和承包商）受益，从而优先考虑对现有水管的检查和修复计划。

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