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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 |