Power Consumption Estimation using In-Memory Database Computation

dc.authorid DAG, HASAN/0000-0001-6252-1870
dc.authorwosid DAG, HASAN/T-5301-2018
dc.contributor.author Dag, Hasan
dc.contributor.author Dağ, Hasan
dc.contributor.author Alamin, Mohamed
dc.contributor.other Management Information Systems
dc.date.accessioned 2024-10-15T19:39:47Z
dc.date.available 2024-10-15T19:39:47Z
dc.date.issued 2016
dc.department Kadir Has University en_US
dc.department-temp [Dag, Hasan; Alamin, Mohamed] Kadir Has Univ, Management Informat Syst Dept, Istanbul, Turkey en_US
dc.description DAG, HASAN/0000-0001-6252-1870 en_US
dc.description.abstract In order to efficiently predict electricity consumption, we need to improve both the speed and the reliability of computational environment. Concerning the speed, we use inmemory database, which is taught to be the best solution that allows manipulating data many times faster than the hard disk. For reliability, we use machine learning algorithms. Since the model performance and accuracy may vary depending on data each time, we test many algorithms and select the best one. In this study, we use SmartMeter Energy Consumption Data in London Households to predict electricity consumption using machine learning algorithms written in Python programming language and in-memory database computation package, Aerospike. The test results show that the best algorithm for our data set is Bagging algorithm. We also emphatically prove that R-squared may not always be a good test to choose the best algorithm. en_US
dc.description.woscitationindex Conference Proceedings Citation Index - Science
dc.identifier.citationcount 0
dc.identifier.endpage 169 en_US
dc.identifier.isbn 9781509037841
dc.identifier.startpage 164 en_US
dc.identifier.uri https://hdl.handle.net/20.500.12469/6346
dc.identifier.wos WOS:000391440600031
dc.language.iso en en_US
dc.publisher Ieee en_US
dc.relation.ispartof 13th HONET-ICT International Symposium on Smart MicroGrids for Sustainable Energy Sources enabled by Photonics and IoT Sensors -- OCT 13-14, 2016 -- Nicosia, CYPRUS en_US
dc.relation.publicationcategory Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.subject In-Memory Database en_US
dc.subject Machine Learning en_US
dc.subject Power Consumption en_US
dc.title Power Consumption Estimation using In-Memory Database Computation en_US
dc.type Conference Object en_US
dc.wos.citedbyCount 0
dspace.entity.type Publication
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