Household Classification Using Smart Meter Data
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|Carroll_Estimating Household Composition from Smart Meter Data_JOS_Sept2017_preprint.pdf||854.83 kB||Adobe PDF||Download|
|Title:||Household Classification Using Smart Meter Data||Authors:||Carroll, Paula
|Permanent link:||http://hdl.handle.net/10197/10383||Date:||1-Mar-2018||Online since:||2019-05-09T10:22:44Z||Abstract:||This article describes a project conducted in conjunction with the Central Statistics Office of Ireland in response to a planned national rollout of smart electricity metering in Ireland. We investigate how this new data source might be used for the purpose of official statistics production. This study specifically looks at the question of determining household composition from electricity smart meter data using both Neural Networks (a supervised machine learning approach) and Elastic Net Logistic regression. An overview of both classification techniques is given. Results for both approaches are presented with analysis. We find that the smart meter data alone is limited in its capability to distinguish between household categories but that it does provide some useful insights.||Type of material:||Journal Article||Publisher:||Sciendo||Journal:||Journal of Official Statistics||Volume:||34||Issue:||1||Start page:||1||End page:||25||Copyright (published version):||2018 the Authors||Keywords:||Neural network; Elastic net logistic regression; Classification system; Household composition; Smart meter data||DOI:||10.1515/jos-2018-0001||Language:||en||Status of Item:||Peer reviewed|
|Appears in Collections:||Business Research Collection|
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