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Prediction of pipe failure rate in Tehran water distribution networks by applying regression models

机译:应用回归模型预测德黑兰供水网络的管道故障率

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摘要

Four statistical models (linear regression, exponential regression, Poisson regression and logistic regression) applied to analyze the variables in pipe vulnerabilities with the objective of finding equations to predict probable future pipe accidents. The most effective variables in pipe failures are material, age, length, diameter and hydraulic pressure. To evaluate these models, the data collected in recent years in the water distribution network of district 1 in Tehran were used, with a total length of 582,702 m of pipes, and 48,500 consumers. The results demonstrate that among the four studied models, the logistic regression model is best able to give a good performance and is capable of predicting future accidents with a higher probability.
机译:四个统计模型(线性回归,指数回归,泊松回归和逻辑回归)用于分析管道脆弱性变量,目的是找到方程式以预测可能的未来管道事故。管道故障中最有效的变量是材料,寿命,长度,直径和液压。为了评估这些模型,使用了近年来在德黑兰1区供水网络中收集的数据,管道总长度为582,702 m,有48,500个用户。结果表明,在所研究的四个模型中,逻辑回归模型最能提供良好的性能,并且能够以更高的概率预测未来的事故。

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