Predicting Electricity Outages Caused by Convective Storms

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorTervo, Roopeen_US
dc.contributor.authorKarjalainen, Joonasen_US
dc.contributor.authorJung, Alexanderen_US
dc.contributor.departmentDepartment of Computer Scienceen
dc.contributor.groupauthorProfessorship Jung Alexanderen
dc.contributor.organizationFinnish Meteorological Instituteen_US
dc.date.accessioned2018-12-10T10:22:56Z
dc.date.available2018-12-10T10:22:56Z
dc.date.issued2018-08-17en_US
dc.description.abstractWe consider the problem of predicting power outages in an electrical power grid due to hazards produced by convective storms. These storms produce extreme weather phenomena such as intense wind, tornadoes and lightning over a small area. In this paper, we discuss the application of state-of-the-art machine learning techniques, such as random forest classifiers and deep neural networks, to predict the amount of damage caused by storms. We cast this application as a classification problem where the goal is to classify storm cells into a finite number of classes, each corresponding to a certain amount of expected damage. The classification method use as input features estimates for storm cell location and movement which has to be extracted from the raw data. A main challenge of this application is that the training data is heavily imbalanced as the occurrence of extreme weather events is rare. In order to address this issue, we applied SMOTE technique.en
dc.description.versionPeer revieweden
dc.format.extent5
dc.format.extent145-149
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationTervo, R, Karjalainen, J & Jung, A 2018, Predicting Electricity Outages Caused by Convective Storms . in 2018 IEEE Data Science Workshop, DSW 2018 - Proceedings ., 8439906, IEEE, pp. 145-149, IEEE Data Science Workshop, Lausanne, Switzerland, 04/06/2018 . https://doi.org/10.1109/DSW.2018.8439906en
dc.identifier.doi10.1109/DSW.2018.8439906en_US
dc.identifier.isbn9781538644102
dc.identifier.otherPURE UUID: 88a8c200-07bd-4389-b256-43058d9cf440en_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/88a8c200-07bd-4389-b256-43058d9cf440en_US
dc.identifier.otherPURE LINK: http://www.scopus.com/inward/record.url?scp=85053131077&partnerID=8YFLogxKen_US
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/28460896/SCI_Tervo_Predicting_Electricity_1805.07897.pdfen_US
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/35142
dc.identifier.urnURN:NBN:fi:aalto-201812106157
dc.language.isoenen
dc.relation.ispartofIEEE Data Science Workshopen
dc.relation.ispartofseries2018 IEEE Data Science Workshop, DSW 2018 - Proceedingsen
dc.rightsopenAccessen
dc.subject.keywordMultilayer Perceptronen_US
dc.subject.keywordNeural Networken_US
dc.subject.keywordPower distributionen_US
dc.subject.keywordRandom Forest Classifieren_US
dc.subject.keywordWeather Impacten_US
dc.titlePredicting Electricity Outages Caused by Convective Stormsen
dc.typeA4 Artikkeli konferenssijulkaisussafi
dc.type.versionacceptedVersion

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