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An Empirical Model for the Prediction of Structural Behavior of Wastewater Collection Systems

机译:废水收集系统结构行为预测的经验模型

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Structural condition of wastewater pipelines is often reported in terms of internal condition grades of 1 through 5, with 1 being the best and 5 the worst condition. The existing models and methodologies for structural deterioration of wastewater pipelines based on ordinary regression or ordinal probit regression violate the model assumptions, and lead to invalid results. Furthermore, the existing ordinal probit models for structural deterioration of Civil infrastructure are overly complex in terms of number of parameters to be estimated. This also makes the interpretation of these models fairly challenging. Another existing modeling technique based on binary logistic regression dichotomizes the data into pass/fail categories, and thus ignores the rank order information available in data.rnThis paper demonstrates the shortcomings of existing methodologies, and presents an ordinal regression model based on cumulative logits with partial proportional odds for modeling the structural degradation behavior of wastewater pipelines. The proposed model is more parsimonious as compared to the existing ordinal probit models as less number of parameters needs to be estimated. The model is also more flexible as it does not assume an overly strict assumption of normally distributed error terms. The model also affords simple interpretation in terms of odds and predicted probabilities. Application, parameters estimation, verification of assumptions, graphical interpretation, and model validation has been demonstrated with real data from the City of Niagara Falls' wastewater collection system. The paper concludes with a discussion of the salient features of the proposed model, and its implications for wastewater systems' performance prediction research.
机译:通常以内部条件等级1到5来报告废水管道的结构条件,其中1是最佳条件,5是最差条件。现有的基于普通回归或序数概率回归的废水管道结构退化模型和方法违反了模型假设,并导致无效的结果。此外,就估计的参数数量而言,现有的用于民用基础设施结构恶化的序数概率模型过于复杂。这也使得对这些模型的解释颇具挑战性。现有的另一种基于二进制逻辑回归的建模技术将数据分为通过/失败类别,从而忽略了数据中可用的排名信息。rn本文展示了现有方法的不足之处,并提出了一种基于累积logit的有序回归模型。用于模拟废水管道结构退化行为的比例赔率。与现有的序数概率模型相比,提出的模型更加简约,因为需要估计的参数数量更少。该模型也更灵活,因为它没有对正态分布误差项进行过严格的假设。该模型还提供了赔率和预测概率的简单解释。尼亚加拉瀑布城废水收集系统的真实数据已证明了其应用,参数估计,假设验证,图形解释和模型验证。本文最后讨论了该模型的显着特征,及其对废水系统性能预测研究的意义。

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