dc.contributor.author | Wu, Di | |
dc.contributor.author | Wang, Hao | |
dc.contributor.author | Seidu, Razak | |
dc.date.accessioned | 2020-01-20T09:15:17Z | |
dc.date.available | 2020-01-20T09:15:17Z | |
dc.date.created | 2019-11-26T21:47:00Z | |
dc.date.issued | 2019 | |
dc.identifier.isbn | 978-1-7281-3024-8 | |
dc.identifier.uri | http://hdl.handle.net/11250/2636939 | |
dc.description.abstract | Drinking Water Supply (DWS) is one of the most critical and sensitive systems to maintain city operations globally. In Europe, the contradiction between the fast growth of population and obsolete urban water supply infrastructure is even more prominent. The high standard water quality requirement not only provides convenience for people's daily life but also challenges the risk response time in the systems. Prevalent water quality regulations are relying on periodic parameter tests. This brings the danger in bacteria broadcast within the testing process which can last for 24-48 hours. In order to cope with these problems, we propose a tensor model for water quality assessment. This model consists of three dimensions, including water quality parameters, locations and time. Furthermore, we applied this model to predict water quality changes in the DWS system using a Random Forest algorithm. For a case study, we select an industrial water supply system in Oslo, Norway. The preliminary results show that this model can provide early warning for water quality risks. | nb_NO |
dc.language.iso | eng | nb_NO |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | nb_NO |
dc.relation.ispartof | Proceedings of IEEE 5th International Conference on Cloud and Big Data Computing (CBDCom 2019) | |
dc.title | A Tensor Model for Quality Analysis in Industrial Drinking Water Supply System | nb_NO |
dc.type | Chapter | nb_NO |
dc.description.version | acceptedVersion | nb_NO |
dc.source.pagenumber | 1090-1092 | nb_NO |
dc.identifier.doi | 10.1109/DASC/PiCom/CBDCom/CyberSciTech.2019.00196 | |
dc.identifier.cristin | 1752810 | |
dc.description.localcode | © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | nb_NO |
cristin.unitcode | 194,63,55,0 | |
cristin.unitcode | 194,63,10,0 | |
cristin.unitcode | 194,64,93,0 | |
cristin.unitname | Institutt for IKT og realfag | |
cristin.unitname | Institutt for datateknologi og informatikk | |
cristin.unitname | Institutt for havromsoperasjoner og byggteknikk | |
cristin.ispublished | true | |
cristin.fulltext | postprint | |
cristin.qualitycode | 1 | |