Assessment of Infrastructure Inspection Needs Using Logistic Models
Assessment of Infrastructure Inspection Needs Using Logistic Models
复制标题
使用逻辑模型评估基础设施检查需求
DOI：
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发表时间：
2001
期刊：
影响因子：
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通讯作者：
Yuqing Yang
中科院分区：
文献类型：
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作者：
S. Ariaratnam;A. El;Yuqing Yang
在基础设施管理领域使用各种退化模型为决策者提供了预测未来退化的工具。本文提出了一种方法来预测的可能性，一个特定的基础设施系统是在一个缺陷的状态，使用逻辑回归模型，线性回归的特殊情况。这两个模型的区别在于逻辑回归模型中的结果变量是二进制或二分的，并假设伯努利分布。该方法是说明在一个案例研究，涉及当地下水道的埃德蒙顿，阿尔塔的评价，加拿大年龄，直径，材料，废物类型和平均覆盖深度的变量进行建模，使用历史数据，作为导致下水道网络恶化的因素。该模型的结果不产生预测的条件评级，而是使用历史检查记录，为决策者提供一种手段，评估下水道部分的规划，未来的定期检查，根据缺陷概率。
Use of various deterioration models in the area of infrastructure management has provided decision makers with a vehicle for predicting future deterioration. This paper presents a methodology for predicting the likelihood that a particular infrastructure system is in a deficient state, using logistic regression models, a special case of linear regression. What distinguishes these two models is that the outcome variable in the logistic regression model is binary or dichotomous and assumes a Bernoulli distribution. The methodology is illustrated in a case study involving the evaluation of the local sewer of Edmonton, Alta., Canada. Variables of age, diameter, material, waste type, and average depth of cover are modeled, using historical data, as factors contributing to deterioration of the sewer network. The outcome of this model does not produce a prediction of condition rating but rather uses historical inspection records to provide decision makers with a means of evaluating sewer sections for the planning of future scheduled inspection, based on the deficiency probability.