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Using machine learning ensemble method for detection of energy theft in smart meters

Referentgranskad
Öppen tillgång
DOI
10.1049/gtd2.12997
Kawoosa, Asif Iqbal; Prashar, Deepak; Faheem, Muhammad; Jha, Nishant; Khan, Arfat Ahmad
Iet generation transmission and distribution2023Publicationer information ikon

Utilizing smart meters in LV network management

Referentgranskad
Löf, Niklas; Pikkarainen, Marko; Repo, Sami; Järventausta, Pertti
International Conference and Exhibition on Electricity Distribution CIRED2011Publicationer information ikon

Unveiling the Decision-Making Dilemmas in Mini-Grids: The Intricate Case of Smart Meters

Referentgranskad
Öppen tillgång
DOI
10.3390/en16176112
Bandi, Venkata; Sahrakorpi, Tiia; Paatero, Jukka; Lahdelma, Risto
Energies2023Publicationer information ikon

Sustainability or instant gratification? A study on Chinese perspectives of ‘pay-as-you-use’ smart energy meters in budget hotels

Referentgranskad
DOI
10.1177/14673584241309215
Lu, Lan; Ma, Chang; Hall, C. Michael
Tourism and hospitality research2024Publicationer information ikon

Reliable Industry 4.0 Based on Machine Learning and IoT for Analyzing, Monitoring, and Securing Smart Meters

Referentgranskad
Öppen tillgång
DOI
10.3390/s21020487
Elsisi, Mahmoud; Mahmoud, Karar; Lehtonen, Matti; Darwish, Mohamed M. F.
Sensors2021Publicationer information ikon

Odd Meters

Mikko Niemistö; Elina Lifländer
-2020Publicationer information ikon

Examples of electromagnetic field(50-100kHz) emissions from smart meters in Finland

Referentgranskad
Pääkkönen R;Lundstöm M;Mustaparta J;Korpinen L
Radioprotection2015Publicationer information ikon

Comparison study of the use non-destructive pavement density meters for dense asphalt barriers

Referentgranskad
Alatyppö, Ville; Elohaka, Eetu
Liverpool John Moores University2007Publicationer information ikon

Joint sampling-communication strategies for smart-meters to aggregator link as secondary users

Referentgranskad
DOI
10.1109/ENERGYCON.2016.7514023
Tomé, Mauricio C.; Nardelli, Pedro H. J.; Alves, Hirley; Latva-aho, Matti
IEEE International Energy Conference2016Publicationer information ikon

Examples of electromagnetic field (50–100 kHz) emissions from smart meters in Finland

Referentgranskad
DOI
10.1051/radiopro/2015004
Pääkkönen, Rauno;Lundström, Marko;Mustaparta, Jari ;Korpinen, Leena
Radioprotection2015

Using machine learning ensemble method for detection of energy theft in smart meters

Referentgranskad
Öppen tillgång
DOI
10.1049/gtd2.12997
2023

Utilizing smart meters in LV network management

Referentgranskad
2011

Unveiling the Decision-Making Dilemmas in Mini-Grids: The Intricate Case of Smart Meters

Referentgranskad
Öppen tillgång
DOI
10.3390/en16176112
2023

Sustainability or instant gratification? A study on Chinese perspectives of ‘pay-as-you-use’ smart energy meters in budget hotels

Referentgranskad
DOI
10.1177/14673584241309215
2024

Reliable Industry 4.0 Based on Machine Learning and IoT for Analyzing, Monitoring, and Securing Smart Meters

Referentgranskad
Öppen tillgång
DOI
10.3390/s21020487
2021

Odd Meters

2020

Examples of electromagnetic field(50-100kHz) emissions from smart meters in Finland

Referentgranskad
2015

Comparison study of the use non-destructive pavement density meters for dense asphalt barriers

Referentgranskad
2007

Joint sampling-communication strategies for smart-meters to aggregator link as secondary users

Referentgranskad
DOI
10.1109/ENERGYCON.2016.7514023
2016

Examples of electromagnetic field (50–100 kHz) emissions from smart meters in Finland

Referentgranskad
DOI
10.1051/radiopro/2015004
2015