Improving data partition schemes in Smart Grids via clustering data streams
详细信息 查看全文
- 作者：Andreu Sancho-Asensioa ; andreus@salleurl.edu" class="auth_mail ; Joan Navarrob ; jnavarro@salleurl.edu" class="auth_mail ; Itziar Arrieta-Salinasc ; itziar.arrieta@unavarra.es" class="auth_mail ; José ; Enrique Armendá ; riz-Í ; ñ ; igoc ; enrique.armendariz@unavarra.es" class="auth_mail ; Virginia Jimé ; nez-Ruanoc ; virginiaj@salleurl.edu" class="auth_mail ; Agustí ; n Zaballosb ; zaballos@salleurl.edu" class="auth_mail ; Elisabet Golobardesa ; elisabet@salleurl.edu" class="auth_mail
- 关键词：Smart Grids ; Data partitions ; Online learning ; Clustering data streams ; Learning classifier systems
- 刊名：Expert Systems with Applications
- 出版年：1 October 2014
- 年：2014
- 卷：41
- 期：13
- 页码：5832-5842
- 全文大小：1409 K
文摘
- •
An online unsupervised LCS algorithm suitable for clustering problems is proposed.
- •
The problem of partitioning the data storage layer on a Smart Grid is explored.
- •
Data partitioning using online clustering boosts the storage layer scalability.
- •
The competence of this approach is assessed using synthetic and real data streams.