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Analysis of PDA-based Water Distribution System Suspension Risk using statistical and machine learning method

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Analysis of PDA-based Water Distribution System Suspension Risk using statistical and machine learning method

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dc.contributor.author Oh, Yoojin es_ES
dc.contributor.author Park, Haekeum es_ES
dc.contributor.author Hyung, Jinseok es_ES
dc.contributor.author Kim, Taehyeon es_ES
dc.contributor.author Kim, Kibum es_ES
dc.contributor.author Koo, Jayong es_ES
dc.date.accessioned 2024-07-15T10:48:45Z
dc.date.available 2024-07-15T10:48:45Z
dc.date.issued 2024-03-06
dc.identifier.isbn 9788490489826
dc.identifier.uri http://hdl.handle.net/10251/206122
dc.description.abstract [EN] Recently, there have been frequent cases of water shortages caused by failure to old water pipes. As water is the most basic resource in life and is an indispensable resource in various fields such as industry and agriculture, the scale of the failure is significant in the event of accidents in the water supply pipe network, and in order to minimize the damage of accidents, it is important to prevent accidents through timely maintenance. At this time, the risk map of the water shortage of the water pipeline needs to be prepared for efficient maintenance, and it needs to be managed first from the high-risk area.To this end, water shortage risk analysis due to pipe failure was performed in this study. Risk analysis is one of the ways in which water pipes are evaluated and decisions on investment plans, such as replacement or repair, can be supported. The risk is generally calculated by multiplying PoF (Probability of failure) with the resulting direct and indirect effects of CoF (Consequence of failure). In this study, PoF was derived as the failure of an individual water pipe was set as the probability of failure caused by corrosion, and in order for it to be predicted, MLP (Multi-layer perceptron) and XGBoot were developed as a data-based machine learning model. In addition, it was analyzed by setting the amount of water (supply shortage) that CoF could not be supplied due to failure, considering that the failure to the water pipe was directly linked to water shortage. In order to analyze the supply shortage at this time, the mathematical analysis of PDA (Pressure driven analysis) was performed.Finally, the developed methodology was applied to the cities of the Republic of Korea, and the risks were analyzed by calculating the PoF and CoF of individual water pipes, and the GIS technique was used to create the risk map.The results of this study can be more accurate in predicting the condition of water pipes, which can be helpful when water utilities establish maintenance plans. es_ES
dc.description.sponsorship The Korea Ministry of Environment supported this work titled as “Project for developing innovative drinking water and wastewater technologies (2020002700016)”. es_ES
dc.format.extent 6 es_ES
dc.language Inglés es_ES
dc.publisher Editorial Universitat Politècnica de València es_ES
dc.relation info:eu-repo/grantAgreement/MESK//2020002700016/Project for developing innovative drinking water and wastewater technologies es_ES
dc.relation.ispartof 2nd International Join Conference on Water Distribution System Analysis (WDSA) & Computing and Control in the Water Industry (CCWI)
dc.rights Reconocimiento - No comercial - Compartir igual (by-nc-sa) es_ES
dc.subject Water Distribution System es_ES
dc.subject Risk analysis es_ES
dc.subject Risk map es_ES
dc.subject Logistic regression es_ES
dc.subject XGBoost regression es_ES
dc.subject Pressure Driven Analysis(PDA) es_ES
dc.title Analysis of PDA-based Water Distribution System Suspension Risk using statistical and machine learning method es_ES
dc.type Capítulo de libro es_ES
dc.type Comunicación en congreso es_ES
dc.identifier.doi 10.4995/WDSA-CCWI2022.2022.14766
dc.rights.accessRights Abierto es_ES
dc.description.bibliographicCitation Oh, Y.; Park, H.; Hyung, J.; Kim, T.; Kim, K.; Koo, J. (2024). Analysis of PDA-based Water Distribution System Suspension Risk using statistical and machine learning method. Editorial Universitat Politècnica de València. https://doi.org/10.4995/WDSA-CCWI2022.2022.14766 es_ES
dc.description.accrualMethod OCS es_ES
dc.relation.conferencename 2nd WDSA/CCWI Joint Conference es_ES
dc.relation.conferencedate Julio 18-22, 2022 es_ES
dc.relation.conferenceplace Valencia, España es_ES
dc.relation.publisherversion http://ocs.editorial.upv.es/index.php/WDSA-CCWI/WDSA-CCWI2022/paper/view/14766 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.relation.pasarela OCS\14766 es_ES
dc.contributor.funder Ministry of environment (South Korea) es_ES


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