Training with synthesised data for disaggregated event classification at the water meter

作者：

Highlights：

• We compare SVM, ANN and KNN classifiers for water meter dissagregation.

• We compare classifiers trained with collected data against synthesised data.

• Training classifiers with synthesised data can improve classification.

• Using synthesised data can reduce configuration time for dissagregation techniques.

摘要

•We compare SVM, ANN and KNN classifiers for water meter dissagregation.•We compare classifiers trained with collected data against synthesised data.•Training classifiers with synthesised data can improve classification.•Using synthesised data can reduce configuration time for dissagregation techniques.

论文关键词：Training data synthesis,Machine learning,Load disaggregation,Assisted living

论文评审过程：Received 25 February 2014, Revised 7 August 2015, Accepted 10 August 2015, Available online 28 August 2015, Version of Record 20 October 2015.

论文官网地址：https://doi.org/10.1016/j.eswa.2015.08.033