Improving data partition schemes in Smart Grids via clustering data streams

作者：

Highlights：

• 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.

摘要

•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.

论文关键词：Smart Grids,Data partitions,Online learning,Clustering data streams,Learning classifier systems

论文评审过程：Available online 1 April 2014.

论文官网地址：https://doi.org/10.1016/j.eswa.2014.03.035